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About the Role We are looking for a hands-on Senior Security Engineer responsible for strengthening the security of our end-user environment and infrastructure across on-premises, data center, and cloud environments. This role will focus primarily on endpoint security, infrastructure and network security, vulnerability management, incident response, Zero Trust, and security automation. The ideal candidate should also have practical experience applying AI technologies to improve security operations, threat detection, investigation, and automation. What You'll Do: Own and continuously improve the security of end-user devices and enterprise infrastructure. Deploy, manage, and optimize endpoint security and EDR solutions such as CrowdStrike or equivalent. Manage endpoint protection, device hardening, security configurations, and endpoint vulnerability remediation. Manage and improve Data Loss Prevention (DLP), secure web/cloud proxy, and other end-user security controls. Implement and continuously improve Zero Trust security principles across users, endpoints, applications, and infrastructure. Work with Identity and Access Management (IAM) and Privileged Access Management (PAM) solutions to secure user and administrative access. Manage and improve network security controls, including firewalls, IDS/IPS, WAF, network segmentation, and secure remote access. Understand network architecture, protocols, and traffic flows and identify opportunities to strengthen network security. Secure Linux-based infrastructure and work with infrastructure teams on system hardening, secure configurations, and access controls. Identify security vulnerabilities, misconfigurations, and infrastructure security gaps and drive remediation with the appropriate engineering teams. Own and support vulnerability management across endpoints, servers, network devices, and infrastructure. Participate in vulnerability assessments, penetration testing, security scans, and remediation activities. Monitor and investigate security alerts using SIEM, EDR, network security, and other security platforms. Participate in security incident response, including investigation, containment, remediation, recovery, and root-cause analysis. Work closely with Infrastructure, Network, IT, SRE, Cloud, and Engineering teams to ensure security is incorporated into architecture and design. Perform security reviews of infrastructure changes, new technologies, and architecture designs. Support security across on-premises, data center, private-cloud, and public-cloud environments. Evaluate new security technologies and work with vendors on technical evaluations and proof-of-concept deployments. Develop and maintain security standards, technical procedures, hardening guidelines, and operational documentation. Mentor junior security engineers and help improve the team's overall technical capabilities. Stay current with emerging cybersecurity threats, technologies, and attack techniques. AI & Security Automation Responsibilities Apply AI technologies and AI-assisted security tools to improve day-to-day security operations. Use AI/ML capabilities for anomaly detection, threat detection, vulnerability prioritization, incident investigation, and security monitoring. Leverage AI to improve security alert analysis, correlation, prioritization, and remediation. Identify opportunities to use AI to reduce repetitive manual security activities and improve operational efficiency. Use AI-assisted approaches to accelerate incident investigation, root-cause analysis, and remediation. Understand security risks introduced by AI and LLM-based applications and recommend appropriate security controls. Understand common AI/LLM security risks, including prompt injection, sensitive-data leakage, unauthorized access, excessive permissions, and misuse of AI systems. Integrate AI capabilities with security platforms, APIs, SIEM/SOAR, monitoring systems, or internal security workflows where appropriate. Develop security automation using Python, Bash, APIs, SOAR, or similar technologies. Participate in security assessments of new AI/LLM technologies being introduced into the organization. Evaluate AI-enabled cybersecurity products and conduct POCs to determine their effectiveness and operational value. We'd Love for You to Have Must have: 8+ years of hands-on experience in cybersecurity, infrastructure security, network security, or related areas. Strong hands-on experience with endpoint security and EDR solutions such as CrowdStrike or equivalent. Strong understanding of endpoint hardening and end-user security. Experience with DLP and secure web/cloud proxy technologies. Good understanding and practical experience implementing Zero Trust security principles. Experience with Identity and Access Management (IAM) and Privileged Access Management (PAM). Strong understanding of network security, firewalls, IDS/IPS, WAF, network segmentation, and networking concepts. Strong understanding of network protocols, architecture, and traffic flows. Experience securing Linux-based systems and infrastructure. Strong experience with vulnerability management and remediation. Experience with security incident investigation and incident response. Working knowledge of SIEM and security monitoring platforms. Experience securing on-premises and data center infrastructure. Working knowledge of at least one major public-cloud platform, preferably AWS. Ability to review infrastructure and network architecture from a security perspective. Practical experience using AI or AI-assisted technologies within cybersecurity or security operations. Understanding of AI/LLM security risks and how AI technologies can affect enterprise security. Experience applying AI to areas such as anomaly detection, security monitoring, incident investigation, vulnerability management, or security automation. Experience with scripting and automation using Python, Bash, APIs, or similar technologies. Strong troubleshooting, analytical, and problem-solving skills. Ability to work effectively with Infrastructure, Network, IT, SRE, Cloud, and Engineering teams. Experience working with global teams. Strong communication skills and ability to explain security risks and remediation requirements to technical teams and management. Good to have: Experience with Darktrace or other Network Detection and Response (NDR) platforms. Experience with SOAR and security orchestration/automation. Kubernetes and container security experience. Experience across AWS, Azure, or GCP security. Experience with VAPT and Red Team/Blue Team exercises. Experience with security architecture and threat modeling. Experience performing AI/LLM security assessments and threat modeling. Experience securing enterprise GenAI/LLM applications, AI agents, RAG systems, or internally developed AI solutions. Familiarity with AI security frameworks and guidance such as MITRE ATLAS, NIST AI RMF, and OWASP guidance for LLM/GenAI applications. Experience supporting ISO 27001, SOC 2, or similar security and compliance programs. Experience evaluating new security products and working with vendors on security POCs. Relevant cybersecurity, network, cloud, or infrastructure certifications are a plus. Qualifications: Bachelor's degree in computer science, Information Technology, Engineering, Cybersecurity, or an equivalent technical field. 6+ years of relevant cybersecurity or infrastructure security experience. Strong hands-on technical background with the ability to independently troubleshoot and resolve complex security issues. Ability to balance security requirements with infrastructure reliability, operational requirements, and business needs. Additional Information: Return to Office : PubMatic employees throughout the global have returned to our offices via a hybrid work schedule (3 days “in office” and 2 days “working remotely”) that is intended to maximize collaboration, innovation, and productivity among teams and across functions. Benefits : Our benefits package includes the best of what leading organizations provide, such as paternity/maternity leave, healthcare insurance, broadband reimbursement. As well, when we’re back in the office, we all benefit from a kitchen loaded with healthy snacks and drinks and catered lunches and much more! Diversity and Inclusion : PubMatic is proud to be an equal opportunity employer; we don’t just value diversity, we promote and celebrate it. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. About PubMatic PubMatic is one of the world’s leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes. Founded in 2006 with the vision that data-driven decisioning would be the future of digital advertising, we enable content creators to run a more profitable advertising business, which in turn allows them to invest back into the multi-screen and multi-format content that consumers demand.

About the Role We are looking for a hands-on Senior Security Engineer responsible for strengthening the security of our end-user environment and infrastructure across on-premises, data center, and cloud environments. This role will focus primarily on endpoint security, infrastructure and network security, vulnerability management, incident response, Zero Trust, and security automation. The ideal candidate should also have practical experience applying AI technologies to improve security operations, threat detection, investigation, and automation. What You'll Do: Own and continuously improve the security of end-user devices and enterprise infrastructure. Deploy, manage, and optimize endpoint security and EDR solutions such as CrowdStrike or equivalent. Manage endpoint protection, device hardening, security configurations, and endpoint vulnerability remediation. Manage and improve Data Loss Prevention (DLP), secure web/cloud proxy, and other end-user security controls. Implement and continuously improve Zero Trust security principles across users, endpoints, applications, and infrastructure. Work with Identity and Access Management (IAM) and Privileged Access Management (PAM) solutions to secure user and administrative access. Manage and improve network security controls, including firewalls, IDS/IPS, WAF, network segmentation, and secure remote access. Understand network architecture, protocols, and traffic flows and identify opportunities to strengthen network security. Secure Linux-based infrastructure and work with infrastructure teams on system hardening, secure configurations, and access controls. Identify security vulnerabilities, misconfigurations, and infrastructure security gaps and drive remediation with the appropriate engineering teams. Own and support vulnerability management across endpoints, servers, network devices, and infrastructure. Participate in vulnerability assessments, penetration testing, security scans, and remediation activities. Monitor and investigate security alerts using SIEM, EDR, network security, and other security platforms. Participate in security incident response, including investigation, containment, remediation, recovery, and root-cause analysis. Work closely with Infrastructure, Network, IT, SRE, Cloud, and Engineering teams to ensure security is incorporated into architecture and design. Perform security reviews of infrastructure changes, new technologies, and architecture designs. Support security across on-premises, data center, private-cloud, and public-cloud environments. Evaluate new security technologies and work with vendors on technical evaluations and proof-of-concept deployments. Develop and maintain security standards, technical procedures, hardening guidelines, and operational documentation. Mentor junior security engineers and help improve the team's overall technical capabilities. Stay current with emerging cybersecurity threats, technologies, and attack techniques. AI & Security Automation Responsibilities Apply AI technologies and AI-assisted security tools to improve day-to-day security operations. Use AI/ML capabilities for anomaly detection, threat detection, vulnerability prioritization, incident investigation, and security monitoring. Leverage AI to improve security alert analysis, correlation, prioritization, and remediation. Identify opportunities to use AI to reduce repetitive manual security activities and improve operational efficiency. Use AI-assisted approaches to accelerate incident investigation, root-cause analysis, and remediation. Understand security risks introduced by AI and LLM-based applications and recommend appropriate security controls. Understand common AI/LLM security risks, including prompt injection, sensitive-data leakage, unauthorized access, excessive permissions, and misuse of AI systems. Integrate AI capabilities with security platforms, APIs, SIEM/SOAR, monitoring systems, or internal security workflows where appropriate. Develop security automation using Python, Bash, APIs, SOAR, or similar technologies. Participate in security assessments of new AI/LLM technologies being introduced into the organization. Evaluate AI-enabled cybersecurity products and conduct POCs to determine their effectiveness and operational value. We'd Love for You to Have Must have: 8+ years of hands-on experience in cybersecurity, infrastructure security, network security, or related areas. Strong hands-on experience with endpoint security and EDR solutions such as CrowdStrike or equivalent. Strong understanding of endpoint hardening and end-user security. Experience with DLP and secure web/cloud proxy technologies. Good understanding and practical experience implementing Zero Trust security principles. Experience with Identity and Access Management (IAM) and Privileged Access Management (PAM). Strong understanding of network security, firewalls, IDS/IPS, WAF, network segmentation, and networking concepts. Strong understanding of network protocols, architecture, and traffic flows. Experience securing Linux-based systems and infrastructure. Strong experience with vulnerability management and remediation. Experience with security incident investigation and incident response. Working knowledge of SIEM and security monitoring platforms. Experience securing on-premises and data center infrastructure. Working knowledge of at least one major public-cloud platform, preferably AWS. Ability to review infrastructure and network architecture from a security perspective. Practical experience using AI or AI-assisted technologies within cybersecurity or security operations. Understanding of AI/LLM security risks and how AI technologies can affect enterprise security. Experience applying AI to areas such as anomaly detection, security monitoring, incident investigation, vulnerability management, or security automation. Experience with scripting and automation using Python, Bash, APIs, or similar technologies. Strong troubleshooting, analytical, and problem-solving skills. Ability to work effectively with Infrastructure, Network, IT, SRE, Cloud, and Engineering teams. Experience working with global teams. Strong communication skills and ability to explain security risks and remediation requirements to technical teams and management. Good to have: Experience with Darktrace or other Network Detection and Response (NDR) platforms. Experience with SOAR and security orchestration/automation. Kubernetes and container security experience. Experience across AWS, Azure, or GCP security. Experience with VAPT and Red Team/Blue Team exercises. Experience with security architecture and threat modeling. Experience performing AI/LLM security assessments and threat modeling. Experience securing enterprise GenAI/LLM applications, AI agents, RAG systems, or internally developed AI solutions. Familiarity with AI security frameworks and guidance such as MITRE ATLAS, NIST AI RMF, and OWASP guidance for LLM/GenAI applications. Experience supporting ISO 27001, SOC 2, or similar security and compliance programs. Experience evaluating new security products and working with vendors on security POCs. Relevant cybersecurity, network, cloud, or infrastructure certifications are a plus. Qualifications: Bachelor's degree in computer science, Information Technology, Engineering, Cybersecurity, or an equivalent technical field. 6+ years of relevant cybersecurity or infrastructure security experience. Strong hands-on technical background with the ability to independently troubleshoot and resolve complex security issues. Ability to balance security requirements with infrastructure reliability, operational requirements, and business needs. Additional Information: Return to Office : PubMatic employees throughout the global have returned to our offices via a hybrid work schedule (3 days “in office” and 2 days “working remotely”) that is intended to maximize collaboration, innovation, and productivity among teams and across functions. Benefits : Our benefits package includes the best of what leading organizations provide, such as paternity/maternity leave, healthcare insurance, broadband reimbursement. As well, when we’re back in the office, we all benefit from a kitchen loaded with healthy snacks and drinks and catered lunches and much more! Diversity and Inclusion : PubMatic is proud to be an equal opportunity employer; we don’t just value diversity, we promote and celebrate it. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. About PubMatic PubMatic is one of the world’s leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes. Founded in 2006 with the vision that data-driven decisioning would be the future of digital advertising, we enable content creators to run a more profitable advertising business, which in turn allows them to invest back into the multi-screen and multi-format content that consumers demand.

About the Role PubMatic is looking for engineers with expertise in Generative AI and AI agent development. You will be responsible for building and optimizing advanced AI agents that leverage the latest technologies in Retrieval-Augmented Generation (RAG), vector databases, and large language models (LLMs). You will work on developing state-of-the-art solutions that enhance Generative AI capabilities and enable our platform to handle complex information retrieval, contextual generation, and adaptive interactions. What You'll Do: Lead the design, development, and deployment of AI-driven features. Drive end-to-end ownership—from feasibility analysis and design specifications to execution and release—while ensuring quick iterations based on customer feedback in a fast-paced Agile environment. Spearhead technical design meetings and produce detailed design documents that outline scalable, secure, and robust AI architectures. Ensure that the solutions are aligned with long-term product strategy and technical roadmaps. Implement and optimize LLMs for specific use cases, including fine-tuning models, deploying pre-trained models, and evaluating their performance. Develop AI agents powered by RAG systems, integrating external knowledge sources to improve the accuracy and relevance of generated content. Design, implement, and optimize vector databases (e.g., FAISS, Pinecone, Weaviate) for efficient and scalable vector search, and work on various vector indexing algorithms. Create sophisticated prompts and fine-tune them to improve the performance of LLMs in generating precise and contextually relevant responses. Utilize evaluation frameworks and metrics (e.g., Evals) to assess and improve the performance of generative models and AI systems. Work with data scientists, engineers, and product teams to integrate AI-driven capabilities into customer-facing products and internal tools. Stay up to date with the latest research and trends in LLMs, RAG, and generative AI technologies to drive innovation in the company’s offerings. Continuously monitor and optimize models to improve their performance, scalability, and cost efficiency. We'd Love for You to Have: 2 to 10 years of total experience and strong understanding of LLMs and their underlying principles — transformer architecture, attention mechanisms, and hyperparameter tuning. Proven experience designing and building AI agents, including multi-agent orchestration, tool-use patterns, multi-step planning, and agent memory architectures (short-term and long-term). Hands-on experience with agentic frameworks such as LangGraph, CrewAI, or AutoGen, and familiarity with RAG pipelines that integrate external knowledge sources (documents, databases, APIs). In-depth knowledge of vector databases and indexing algorithms; practical experience with FAISS, Pinecone, Weaviate, or Milvus. Experience with agent observability, tracing, and guardrails — tools like Langfuse or equivalent — to ensure reliability, safety, and debuggability of agentic systems. Proficiency in prompt engineering — crafting, iterating, and optimizing complex prompts for context-sensitive, domain-specific LLM outputs. Familiarity with Evals and other performance evaluation tools for measuring model quality, relevance, and efficiency. Proficiency in Python and experience with machine learning libraries such as TensorFlow, PyTorch, and Hugging Face Transformers. Experience with data preprocessing, vectorization, and handling large-scale datasets. Ability to present complex technical ideas and results to both technical and non-technical stakeholders. Nice-to-Have: Experience in building AI agents using graph-based architectures, including knowledge graph embeddings and graph neural networks (GNNs). Experience with training small base models using custom data, including data collection, pre-processing, and fine-tuning models to specific domains or tasks. Familiarity with deploying AI models on cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). Familiarity with programmatic advertising, RTB, or ad auction mechanics. Knowledge of MCP (Model Context Protocol) or similar tool-integration standards Publication or contributions to research in AI, LLMs, or related fields. Qualification: Should have a bachelor’s degree in engineering or an equivalent degree from a well-known institute/university. Additional Information: Return to Office : PubMatic employees throughout the globe have returned to our offices via a hybrid work schedule (3 days “in office” and 2 days “working remotely”) that is intended to maximize collaboration, innovation, and productivity among teams and across functions. Benefits: Our benefits package includes the best of what leading organizations provide, such as paternity/maternity leave, healthcare insurance, broadband reimbursement. As well, when we’re back in the office, we all benefit from a kitchen loaded with healthy snacks and drinks and catered lunches and much more!. Diversity and Inclusion : PubMatic is proud to be an equal opportunity employer; we don’t just value diversity, we promote and celebrate it. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status About PubMatic PubMatic is one of the world’s leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes. Founded in 2006 with the vision that data-driven decisioning would be the future of digital advertising, we enable content creators to run a more profitable advertising business, which in turn allows them to invest back into the multi-screen and multi-format content that consumers demand.

About the Role PubMatic is seeking an experienced and technically strong Principal Software Engineer to lead the design and development of next-generation Mobile App Monetization capabilities. This role is focused on building high-performance, low-latency, scalable, and privacy-safe systems that help maximize publisher revenue from in-app inventory while improving DSP and buyer spend efficiency. The role requires a deep understanding of mobile app advertising, SSP-DSP RTB workflows, OpenRTB mobile signals, SDK/mediation integrations, traffic shaping, QPS optimization, mobile attribution, privacy constraints, and performance advertising. The engineer will work on systems that monetize mobile formats such as rewarded video, interstitial, native, banner, app-open, playable, and video ads. The ideal candidate is a seasoned backend engineer with strong ad-tech domain expertise and experience building real-time auction, targeting, decisioning, and optimization systems. You will work closely with Product, Data Science, Marketplace Quality, DSP Partnerships, Publisher teams, and SRE to build ML-integrated and data-driven monetization systems that improve yield, bid rate, win rate, fill rate, attribution readiness, latency, and reliability across PubMatic’s mobile app ecosystem. What You'll Do Architect and implement scalable backend services powering mobile app monetization, extracting, transforming, and optimizing in-app behavioral data using on-device computation, data aggregation, and differential privacy techniques so that publishers can still deliver targeted ads and measure performance without accessing persistent, individual user identities. Build and optimize SSP-DSP integration workflows for mobile app inventory, including app bundle validation, device and geo signal handling, privacy-aware user signal processing, bid response handling, loss reason analysis, and DSP-specific troubleshooting. Design mobile-specific traffic shaping and QPS optimization systems that prioritize high-value in-app inventory based on bid probability, win probability, spend potential, app quality, device signals, geo value, ad format, consent availability, and DSP buying behavior. Improve runtime handling for Mobile App ad formats such as rewarded video, interstitial, native, banner, app-open, playable, and in-app video, including format eligibility, creative compatibility, response validation, tracking, completion, and reward-callback correctness. Build capabilities that improve buyer/DSP compatibility for MApp inventory, ensuring buyers receive well-represented, privacy-compliant, format-compatible, attribution-ready, and supply-quality-aware mobile app requests. Develop systems and diagnostics to improve Mobile App supply quality, including app bundle validation, app store metadata checks, app-ads.txt, sellers.json, SupplyChain object validation, app spoofing detection, invalid traffic indicators, device/geo inconsistency checks, and low-quality partner supply detection. Support privacy-aware and attribution-ready Mobile App advertising, including ATT/IDFA handling, AAID availability, consent enforcement, COPPA/child-directed treatment, SKAN readiness, MMP signal passing, click/impression tracking, and privacy-safe fallback when user-level identifiers are unavailable. Partner with MApp SDK and OpenBid/S2S integration teams to define signal-quality standards, request-field expectations, placement/ad-unit semantics, tracking requirements, and partner feedback loops for Mobile App supply. Build publisher-facing and buyer-facing diagnostics for MApp inventory, including missing-field reports, app quality signals, buyer no-bid diagnostics, fill and eCPM diagnostics, tracking mismatch analysis, attribution readiness, and supply-path quality insights. Work with DSP Partnerships and Marketplace Quality teams to improve buyer confidence in PubMatic’s MApp supply by addressing format compatibility, attribution readiness, privacy eligibility, fraud risk, supply transparency, and app inventory quality. Collaborate with Product, Data Science, Publisher teams, DSP Partnerships, Marketplace Quality, MApp SDK, OpenBid/S2S integrations, and SRE to define and execute the roadmap for differentiated Mobile App advertising capabilities. Champion operational excellence for Mobile App advertising systems through strong observability, reason codes, structured logs, dashboards, alerts, safe rollouts, latency protection, production debugging, and cross-team incident response. We'd Love for You to Have Five plus years of backend engineering experience, with a proven track record of building high-scale, low-latency systems, preferably in mobile app advertising, SSP, DSP, ad exchange, mediation, mobile SDK, app-install, or programmatic AdTech domains. Strong knowledge of mobile app inventory signals, including app bundle, app store URL, SDK version, placement type, rewarded indicator, device ID, IDFA, AAID, IDFV, OS version, carrier, connection type, geo, consent status, and ad format metadata. Familiarity with mobile ad formats such as rewarded video, interstitial, native, banner, app-open, playable, and in-app video ads, including how each format impacts pricing, buyer demand, creative rendering, tracking, and user experience. Strong understanding of mobile performance advertising concepts such as app-install campaigns, CPI, CPA, ROAS, retention, lifetime value, post-install events, retargeting where allowed, and buyer outcome optimization. Experience or strong familiarity with mobile attribution and measurement ecosystems, including MMPs, AppsFlyer, Adjust, Singular, Firebase, SKAdNetwork, Android attribution changes, click tracking, impression tracking, and delayed/aggregated conversion signals. Strong knowledge of mobile privacy and compliance constraints, including Apple ATT, IDFA availability, Android Advertising ID, SKAdNetwork, Google Privacy Sandbox for Android, COPPA, GDPR, CCPA/CPRA, TCF, GPP, and do-not-sell/share flags. Practical knowledge of mobile supply quality and fraud prevention, including app bundle spoofing, SDK spoofing, device spoofing, geo mismatch, VPN/proxy traffic, click injection, click spam, invalid traffic, app-ads.txt, sellers.json, and SupplyChain object validation. Excellent interpersonal, written, and verbal communication skills with a collaborative mindset, strong ownership, and ability to work cross-functionally with Product, Data Science, DSP Partnerships, Publisher teams, Marketplace Quality, and SRE. Bonus Qualifications Hands-on experience with mobile monetization SDKs, client-server ad request flows, mediation logic, in-app bidding, server-side bidding, waterfalls, or unified auction systems. Contributions to open-source AdTech projects such as Prebid Mobile, RTBkit, OpenRTB tools, header bidding libraries, or mobile SDK/ad-serving frameworks. Familiarity with industry-standard ML model-serving infrastructure designed for real-time inference in high-QPS, low-latency environments. Understanding of mobile user acquisition, performance DSPs, app-install campaigns, MMP integrations, and attribution platforms. Experience working with incrementality measurement, retargeting systems, audience segmentation, cohort-based optimization, or privacy-safe targeting for mobile performance marketing. Exposure to privacy-preserving user ID solutions such as UID2.0, RampID, publisher first-party IDs, hashed identifiers where allowed, and frameworks such as SKAdNetwork for iOS post-ATT monetization. Experience with cross-format mobile monetization strategies, including combining rewarded video, interstitial, native, banner, app-open, playable, and video monetization within the same app session. Familiarity with real-time analytics pipelines used to measure mobile monetization KPIs such as bid rate, win rate, fill rate, eCPM, revenue, QPS efficiency, timeout rate, attribution feedback, buyer spend, and yield efficiency. Publications, patents, internal platform leadership, or speaking engagements in mobile monetization, AdTech infrastructure, RTB optimization, privacy-safe advertising, or ML for AdTech. Why Join Us? Work on high-scale mobile monetization infrastructure that directly impacts publisher revenue, DSP spend, and advertiser outcomes across the in-app advertising ecosystem. Help shape the future of ML-powered mobile monetization, real-time ad decisioning, traffic shaping, attribution readiness, and privacy-safe performance advertising. Build systems that improve monetization across premium mobile formats such as rewarded video, interstitial, native, banner, app-open, playable, and video ads. Collaborate with industry-leading engineers, product teams, machine learning experts, DSP partners, publisher teams, and marketplace quality teams. Competitive compensation, performance-based incentives, and strong career growth opportunities in a globally recognized AdTech company. AI-Enabled Engineering Mindset: We value engineers who actively leverage Generative AI tools and IDEs (e.g. GitHub Copilot, ChatGPT, Claude, Cursor, Windsurf etc.) to accelerate development, improve code quality, automate repetitive tasks, and enhance documentation and debugging workflows. Engineers who demonstrate AI-first thinking using these tools to drive faster experimentation, ideation, and technical execution will thrive in our high-scale, performance-critical environment. Qualifications: Should have a bachelor’s degree in engineering (CS / IT) or equivalent degree from well-known Institutes / Universities. Additional Information: Return to Office : PubMatic employees throughout the global have returned to our offices via a hybrid work schedule (3 days “in office” and 2 days “working remotely”) that is intended to maximize collaboration, innovation, and productivity among teams and across functions. Benefits : Our benefits package includes the best of what leading organizations provide, such as paternity/maternity leave, healthcare insurance, broadband reimbursement. As well, when we’re back in the office, we all benefit from a kitchen loaded with healthy snacks and drinks and catered lunches and much more! Diversity and Inclusion : PubMatic is proud to be an equal opportunity employer; we don’t just value diversity, we promote and celebrate it. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. About PubMatic PubMatic is one of the world’s leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes. Founded in 2006 with the vision that data-driven decisioning would be the future of digital advertising, we enable content creators to run a more profitable advertising business, which in turn allows them to invest back into the multi-screen and multi-format content that consumers demand.

About the Role PubMatic is seeking an experienced and technically strong Principal Software Engineer to lead the design and development of next-generation Mobile App Monetization capabilities. This role is focused on building high-performance, low-latency, scalable, and privacy-safe systems that help maximize publisher revenue from in-app inventory while improving DSP and buyer spend efficiency. The role requires a deep understanding of mobile app advertising, SSP-DSP RTB workflows, OpenRTB mobile signals, SDK/mediation integrations, traffic shaping, QPS optimization, mobile attribution, privacy constraints, and performance advertising. The engineer will work on systems that monetize mobile formats such as rewarded video, interstitial, native, banner, app-open, playable, and video ads. The ideal candidate is a seasoned backend engineer with strong ad-tech domain expertise and experience building real-time auction, targeting, decisioning, and optimization systems. You will work closely with Product, Data Science, Marketplace Quality, DSP Partnerships, Publisher teams, and SRE to build ML-integrated and data-driven monetization systems that improve yield, bid rate, win rate, fill rate, attribution readiness, latency, and reliability across PubMatic’s mobile app ecosystem. What You'll Do Architect and implement scalable backend services powering mobile app monetization, extracting, transforming, and optimizing in-app behavioral data using on-device computation, data aggregation, and differential privacy techniques so that publishers can still deliver targeted ads and measure performance without accessing persistent, individual user identities. Build and optimize SSP-DSP integration workflows for mobile app inventory, including app bundle validation, device and geo signal handling, privacy-aware user signal processing, bid response handling, loss reason analysis, and DSP-specific troubleshooting. Design mobile-specific traffic shaping and QPS optimization systems that prioritize high-value in-app inventory based on bid probability, win probability, spend potential, app quality, device signals, geo value, ad format, consent availability, and DSP buying behavior. Improve runtime handling for Mobile App ad formats such as rewarded video, interstitial, native, banner, app-open, playable, and in-app video, including format eligibility, creative compatibility, response validation, tracking, completion, and reward-callback correctness. Build capabilities that improve buyer/DSP compatibility for MApp inventory, ensuring buyers receive well-represented, privacy-compliant, format-compatible, attribution-ready, and supply-quality-aware mobile app requests. Develop systems and diagnostics to improve Mobile App supply quality, including app bundle validation, app store metadata checks, app-ads.txt, sellers.json, SupplyChain object validation, app spoofing detection, invalid traffic indicators, device/geo inconsistency checks, and low-quality partner supply detection. Support privacy-aware and attribution-ready Mobile App advertising, including ATT/IDFA handling, AAID availability, consent enforcement, COPPA/child-directed treatment, SKAN readiness, MMP signal passing, click/impression tracking, and privacy-safe fallback when user-level identifiers are unavailable. Partner with MApp SDK and OpenBid/S2S integration teams to define signal-quality standards, request-field expectations, placement/ad-unit semantics, tracking requirements, and partner feedback loops for Mobile App supply. Build publisher-facing and buyer-facing diagnostics for MApp inventory, including missing-field reports, app quality signals, buyer no-bid diagnostics, fill and eCPM diagnostics, tracking mismatch analysis, attribution readiness, and supply-path quality insights. Work with DSP Partnerships and Marketplace Quality teams to improve buyer confidence in PubMatic’s MApp supply by addressing format compatibility, attribution readiness, privacy eligibility, fraud risk, supply transparency, and app inventory quality. Collaborate with Product, Data Science, Publisher teams, DSP Partnerships, Marketplace Quality, MApp SDK, OpenBid/S2S integrations, and SRE to define and execute the roadmap for differentiated Mobile App advertising capabilities. Champion operational excellence for Mobile App advertising systems through strong observability, reason codes, structured logs, dashboards, alerts, safe rollouts, latency protection, production debugging, and cross-team incident response. We'd Love for You to Have Five plus years of backend engineering experience, with a proven track record of building high-scale, low-latency systems, preferably in mobile app advertising, SSP, DSP, ad exchange, mediation, mobile SDK, app-install, or programmatic AdTech domains. Strong knowledge of mobile app inventory signals, including app bundle, app store URL, SDK version, placement type, rewarded indicator, device ID, IDFA, AAID, IDFV, OS version, carrier, connection type, geo, consent status, and ad format metadata. Familiarity with mobile ad formats such as rewarded video, interstitial, native, banner, app-open, playable, and in-app video ads, including how each format impacts pricing, buyer demand, creative rendering, tracking, and user experience. Strong understanding of mobile performance advertising concepts such as app-install campaigns, CPI, CPA, ROAS, retention, lifetime value, post-install events, retargeting where allowed, and buyer outcome optimization. Experience or strong familiarity with mobile attribution and measurement ecosystems, including MMPs, AppsFlyer, Adjust, Singular, Firebase, SKAdNetwork, Android attribution changes, click tracking, impression tracking, and delayed/aggregated conversion signals. Strong knowledge of mobile privacy and compliance constraints, including Apple ATT, IDFA availability, Android Advertising ID, SKAdNetwork, Google Privacy Sandbox for Android, COPPA, GDPR, CCPA/CPRA, TCF, GPP, and do-not-sell/share flags. Practical knowledge of mobile supply quality and fraud prevention, including app bundle spoofing, SDK spoofing, device spoofing, geo mismatch, VPN/proxy traffic, click injection, click spam, invalid traffic, app-ads.txt, sellers.json, and SupplyChain object validation. Excellent interpersonal, written, and verbal communication skills with a collaborative mindset, strong ownership, and ability to work cross-functionally with Product, Data Science, DSP Partnerships, Publisher teams, Marketplace Quality, and SRE. Bonus Qualifications Hands-on experience with mobile monetization SDKs, client-server ad request flows, mediation logic, in-app bidding, server-side bidding, waterfalls, or unified auction systems. Contributions to open-source AdTech projects such as Prebid Mobile, RTBkit, OpenRTB tools, header bidding libraries, or mobile SDK/ad-serving frameworks. Familiarity with industry-standard ML model-serving infrastructure designed for real-time inference in high-QPS, low-latency environments. Understanding of mobile user acquisition, performance DSPs, app-install campaigns, MMP integrations, and attribution platforms. Experience working with incrementality measurement, retargeting systems, audience segmentation, cohort-based optimization, or privacy-safe targeting for mobile performance marketing. Exposure to privacy-preserving user ID solutions such as UID2.0, RampID, publisher first-party IDs, hashed identifiers where allowed, and frameworks such as SKAdNetwork for iOS post-ATT monetization. Experience with cross-format mobile monetization strategies, including combining rewarded video, interstitial, native, banner, app-open, playable, and video monetization within the same app session. Familiarity with real-time analytics pipelines used to measure mobile monetization KPIs such as bid rate, win rate, fill rate, eCPM, revenue, QPS efficiency, timeout rate, attribution feedback, buyer spend, and yield efficiency. Publications, patents, internal platform leadership, or speaking engagements in mobile monetization, AdTech infrastructure, RTB optimization, privacy-safe advertising, or ML for AdTech. Why Join Us? Work on high-scale mobile monetization infrastructure that directly impacts publisher revenue, DSP spend, and advertiser outcomes across the in-app advertising ecosystem. Help shape the future of ML-powered mobile monetization, real-time ad decisioning, traffic shaping, attribution readiness, and privacy-safe performance advertising. Build systems that improve monetization across premium mobile formats such as rewarded video, interstitial, native, banner, app-open, playable, and video ads. Collaborate with industry-leading engineers, product teams, machine learning experts, DSP partners, publisher teams, and marketplace quality teams. Competitive compensation, performance-based incentives, and strong career growth opportunities in a globally recognized AdTech company. AI-Enabled Engineering Mindset: We value engineers who actively leverage Generative AI tools and IDEs (e.g. GitHub Copilot, ChatGPT, Claude, Cursor, Windsurf etc.) to accelerate development, improve code quality, automate repetitive tasks, and enhance documentation and debugging workflows. Engineers who demonstrate AI-first thinking using these tools to drive faster experimentation, ideation, and technical execution will thrive in our high-scale, performance-critical environment. Qualifications: Should have a bachelor’s degree in engineering (CS / IT) or equivalent degree from well-known Institutes / Universities. Additional Information: Return to Office : PubMatic employees throughout the global have returned to our offices via a hybrid work schedule (3 days “in office” and 2 days “working remotely”) that is intended to maximize collaboration, innovation, and productivity among teams and across functions. Benefits : Our benefits package includes the best of what leading organizations provide, such as paternity/maternity leave, healthcare insurance, broadband reimbursement. As well, when we’re back in the office, we all benefit from a kitchen loaded with healthy snacks and drinks and catered lunches and much more! Diversity and Inclusion : PubMatic is proud to be an equal opportunity employer; we don’t just value diversity, we promote and celebrate it. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. About PubMatic PubMatic is one of the world’s leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes. Founded in 2006 with the vision that data-driven decisioning would be the future of digital advertising, we enable content creators to run a more profitable advertising business, which in turn allows them to invest back into the multi-screen and multi-format content that consumers demand.

About the Role PubMatic is seeking an experienced and technically strong Principal Software Engineer to lead the design and development of next-generation Mobile App Monetization capabilities. This role is focused on building high-performance, low-latency, scalable, and privacy-safe systems that help maximize publisher revenue from in-app inventory while improving DSP and buyer spend efficiency. The role requires a deep understanding of mobile app advertising, SSP-DSP RTB workflows, OpenRTB mobile signals, SDK/mediation integrations, traffic shaping, QPS optimization, mobile attribution, privacy constraints, and performance advertising. The engineer will work on systems that monetize mobile formats such as rewarded video, interstitial, native, banner, app-open, playable, and video ads. The ideal candidate is a seasoned backend engineer with strong ad-tech domain expertise and experience building real-time auction, targeting, decisioning, and optimization systems. You will work closely with Product, Data Science, Marketplace Quality, DSP Partnerships, Publisher teams, and SRE to build ML-integrated and data-driven monetization systems that improve yield, bid rate, win rate, fill rate, attribution readiness, latency, and reliability across PubMatic’s mobile app ecosystem. What You'll Do Architect and implement scalable backend services powering mobile app monetization, extracting, transforming, and optimizing in-app behavioral data using on-device computation, data aggregation, and differential privacy techniques so that publishers can still deliver targeted ads and measure performance without accessing persistent, individual user identities. Build and optimize SSP-DSP integration workflows for mobile app inventory, including app bundle validation, device and geo signal handling, privacy-aware user signal processing, bid response handling, loss reason analysis, and DSP-specific troubleshooting. Design mobile-specific traffic shaping and QPS optimization systems that prioritize high-value in-app inventory based on bid probability, win probability, spend potential, app quality, device signals, geo value, ad format, consent availability, and DSP buying behavior. Improve runtime handling for Mobile App ad formats such as rewarded video, interstitial, native, banner, app-open, playable, and in-app video, including format eligibility, creative compatibility, response validation, tracking, completion, and reward-callback correctness. Build capabilities that improve buyer/DSP compatibility for MApp inventory, ensuring buyers receive well-represented, privacy-compliant, format-compatible, attribution-ready, and supply-quality-aware mobile app requests. Develop systems and diagnostics to improve Mobile App supply quality, including app bundle validation, app store metadata checks, app-ads.txt, sellers.json, SupplyChain object validation, app spoofing detection, invalid traffic indicators, device/geo inconsistency checks, and low-quality partner supply detection. Support privacy-aware and attribution-ready Mobile App advertising, including ATT/IDFA handling, AAID availability, consent enforcement, COPPA/child-directed treatment, SKAN readiness, MMP signal passing, click/impression tracking, and privacy-safe fallback when user-level identifiers are unavailable. Partner with MApp SDK and OpenBid/S2S integration teams to define signal-quality standards, request-field expectations, placement/ad-unit semantics, tracking requirements, and partner feedback loops for Mobile App supply. Build publisher-facing and buyer-facing diagnostics for MApp inventory, including missing-field reports, app quality signals, buyer no-bid diagnostics, fill and eCPM diagnostics, tracking mismatch analysis, attribution readiness, and supply-path quality insights. Work with DSP Partnerships and Marketplace Quality teams to improve buyer confidence in PubMatic’s MApp supply by addressing format compatibility, attribution readiness, privacy eligibility, fraud risk, supply transparency, and app inventory quality. Collaborate with Product, Data Science, Publisher teams, DSP Partnerships, Marketplace Quality, MApp SDK, OpenBid/S2S integrations, and SRE to define and execute the roadmap for differentiated Mobile App advertising capabilities. Champion operational excellence for Mobile App advertising systems through strong observability, reason codes, structured logs, dashboards, alerts, safe rollouts, latency protection, production debugging, and cross-team incident response. We'd Love for You to Have Five plus years of backend engineering experience, with a proven track record of building high-scale, low-latency systems, preferably in mobile app advertising, SSP, DSP, ad exchange, mediation, mobile SDK, app-install, or programmatic AdTech domains. Strong knowledge of mobile app inventory signals, including app bundle, app store URL, SDK version, placement type, rewarded indicator, device ID, IDFA, AAID, IDFV, OS version, carrier, connection type, geo, consent status, and ad format metadata. Familiarity with mobile ad formats such as rewarded video, interstitial, native, banner, app-open, playable, and in-app video ads, including how each format impacts pricing, buyer demand, creative rendering, tracking, and user experience. Strong understanding of mobile performance advertising concepts such as app-install campaigns, CPI, CPA, ROAS, retention, lifetime value, post-install events, retargeting where allowed, and buyer outcome optimization. Experience or strong familiarity with mobile attribution and measurement ecosystems, including MMPs, AppsFlyer, Adjust, Singular, Firebase, SKAdNetwork, Android attribution changes, click tracking, impression tracking, and delayed/aggregated conversion signals. Strong knowledge of mobile privacy and compliance constraints, including Apple ATT, IDFA availability, Android Advertising ID, SKAdNetwork, Google Privacy Sandbox for Android, COPPA, GDPR, CCPA/CPRA, TCF, GPP, and do-not-sell/share flags. Practical knowledge of mobile supply quality and fraud prevention, including app bundle spoofing, SDK spoofing, device spoofing, geo mismatch, VPN/proxy traffic, click injection, click spam, invalid traffic, app-ads.txt, sellers.json, and SupplyChain object validation. Excellent interpersonal, written, and verbal communication skills with a collaborative mindset, strong ownership, and ability to work cross-functionally with Product, Data Science, DSP Partnerships, Publisher teams, Marketplace Quality, and SRE. Bonus Qualifications Hands-on experience with mobile monetization SDKs, client-server ad request flows, mediation logic, in-app bidding, server-side bidding, waterfalls, or unified auction systems. Contributions to open-source AdTech projects such as Prebid Mobile, RTBkit, OpenRTB tools, header bidding libraries, or mobile SDK/ad-serving frameworks. Familiarity with industry-standard ML model-serving infrastructure designed for real-time inference in high-QPS, low-latency environments. Understanding of mobile user acquisition, performance DSPs, app-install campaigns, MMP integrations, and attribution platforms. Experience working with incrementality measurement, retargeting systems, audience segmentation, cohort-based optimization, or privacy-safe targeting for mobile performance marketing. Exposure to privacy-preserving user ID solutions such as UID2.0, RampID, publisher first-party IDs, hashed identifiers where allowed, and frameworks such as SKAdNetwork for iOS post-ATT monetization. Experience with cross-format mobile monetization strategies, including combining rewarded video, interstitial, native, banner, app-open, playable, and video monetization within the same app session. Familiarity with real-time analytics pipelines used to measure mobile monetization KPIs such as bid rate, win rate, fill rate, eCPM, revenue, QPS efficiency, timeout rate, attribution feedback, buyer spend, and yield efficiency. Publications, patents, internal platform leadership, or speaking engagements in mobile monetization, AdTech infrastructure, RTB optimization, privacy-safe advertising, or ML for AdTech. Why Join Us? Work on high-scale mobile monetization infrastructure that directly impacts publisher revenue, DSP spend, and advertiser outcomes across the in-app advertising ecosystem. Help shape the future of ML-powered mobile monetization, real-time ad decisioning, traffic shaping, attribution readiness, and privacy-safe performance advertising. Build systems that improve monetization across premium mobile formats such as rewarded video, interstitial, native, banner, app-open, playable, and video ads. Collaborate with industry-leading engineers, product teams, machine learning experts, DSP partners, publisher teams, and marketplace quality teams. Competitive compensation, performance-based incentives, and strong career growth opportunities in a globally recognized AdTech company. AI-Enabled Engineering Mindset: We value engineers who actively leverage Generative AI tools and IDEs (e.g. GitHub Copilot, ChatGPT, Claude, Cursor, Windsurf etc.) to accelerate development, improve code quality, automate repetitive tasks, and enhance documentation and debugging workflows. Engineers who demonstrate AI-first thinking using these tools to drive faster experimentation, ideation, and technical execution will thrive in our high-scale, performance-critical environment. Qualifications: Should have a bachelor’s degree in engineering (CS / IT) or equivalent degree from well-known Institutes / Universities. Additional Information: Return to Office : PubMatic employees throughout the global have returned to our offices via a hybrid work schedule (3 days “in office” and 2 days “working remotely”) that is intended to maximize collaboration, innovation, and productivity among teams and across functions. Benefits : Our benefits package includes the best of what leading organizations provide, such as paternity/maternity leave, healthcare insurance, broadband reimbursement. As well, when we’re back in the office, we all benefit from a kitchen loaded with healthy snacks and drinks and catered lunches and much more! Diversity and Inclusion : PubMatic is proud to be an equal opportunity employer; we don’t just value diversity, we promote and celebrate it. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. About PubMatic PubMatic is one of the world’s leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes. Founded in 2006 with the vision that data-driven decisioning would be the future of digital advertising, we enable content creators to run a more profitable advertising business, which in turn allows them to invest back into the multi-screen and multi-format content that consumers demand.

About the Role PubMatic is seeking an experienced and technically strong Principal Software Engineer to lead the design and development of next-generation Mobile App Monetization capabilities. This role is focused on building high-performance, low-latency, scalable, and privacy-safe systems that help maximize publisher revenue from in-app inventory while improving DSP and buyer spend efficiency. The role requires a deep understanding of mobile app advertising, SSP-DSP RTB workflows, OpenRTB mobile signals, SDK/mediation integrations, traffic shaping, QPS optimization, mobile attribution, privacy constraints, and performance advertising. The engineer will work on systems that monetize mobile formats such as rewarded video, interstitial, native, banner, app-open, playable, and video ads. The ideal candidate is a seasoned backend engineer with strong ad-tech domain expertise and experience building real-time auction, targeting, decisioning, and optimization systems. You will work closely with Product, Data Science, Marketplace Quality, DSP Partnerships, Publisher teams, and SRE to build ML-integrated and data-driven monetization systems that improve yield, bid rate, win rate, fill rate, attribution readiness, latency, and reliability across PubMatic’s mobile app ecosystem. What You'll Do Architect and implement scalable backend services powering mobile app monetization, extracting, transforming, and optimizing in-app behavioral data using on-device computation, data aggregation, and differential privacy techniques so that publishers can still deliver targeted ads and measure performance without accessing persistent, individual user identities. Build and optimize SSP-DSP integration workflows for mobile app inventory, including app bundle validation, device and geo signal handling, privacy-aware user signal processing, bid response handling, loss reason analysis, and DSP-specific troubleshooting. Design mobile-specific traffic shaping and QPS optimization systems that prioritize high-value in-app inventory based on bid probability, win probability, spend potential, app quality, device signals, geo value, ad format, consent availability, and DSP buying behavior. Improve runtime handling for Mobile App ad formats such as rewarded video, interstitial, native, banner, app-open, playable, and in-app video, including format eligibility, creative compatibility, response validation, tracking, completion, and reward-callback correctness. Build capabilities that improve buyer/DSP compatibility for MApp inventory, ensuring buyers receive well-represented, privacy-compliant, format-compatible, attribution-ready, and supply-quality-aware mobile app requests. Develop systems and diagnostics to improve Mobile App supply quality, including app bundle validation, app store metadata checks, app-ads.txt, sellers.json, SupplyChain object validation, app spoofing detection, invalid traffic indicators, device/geo inconsistency checks, and low-quality partner supply detection. Support privacy-aware and attribution-ready Mobile App advertising, including ATT/IDFA handling, AAID availability, consent enforcement, COPPA/child-directed treatment, SKAN readiness, MMP signal passing, click/impression tracking, and privacy-safe fallback when user-level identifiers are unavailable. Partner with MApp SDK and OpenBid/S2S integration teams to define signal-quality standards, request-field expectations, placement/ad-unit semantics, tracking requirements, and partner feedback loops for Mobile App supply. Build publisher-facing and buyer-facing diagnostics for MApp inventory, including missing-field reports, app quality signals, buyer no-bid diagnostics, fill and eCPM diagnostics, tracking mismatch analysis, attribution readiness, and supply-path quality insights. Work with DSP Partnerships and Marketplace Quality teams to improve buyer confidence in PubMatic’s MApp supply by addressing format compatibility, attribution readiness, privacy eligibility, fraud risk, supply transparency, and app inventory quality. Collaborate with Product, Data Science, Publisher teams, DSP Partnerships, Marketplace Quality, MApp SDK, OpenBid/S2S integrations, and SRE to define and execute the roadmap for differentiated Mobile App advertising capabilities. Champion operational excellence for Mobile App advertising systems through strong observability, reason codes, structured logs, dashboards, alerts, safe rollouts, latency protection, production debugging, and cross-team incident response. We'd Love for You to Have Five plus years of backend engineering experience, with a proven track record of building high-scale, low-latency systems, preferably in mobile app advertising, SSP, DSP, ad exchange, mediation, mobile SDK, app-install, or programmatic AdTech domains. Strong knowledge of mobile app inventory signals, including app bundle, app store URL, SDK version, placement type, rewarded indicator, device ID, IDFA, AAID, IDFV, OS version, carrier, connection type, geo, consent status, and ad format metadata. Familiarity with mobile ad formats such as rewarded video, interstitial, native, banner, app-open, playable, and in-app video ads, including how each format impacts pricing, buyer demand, creative rendering, tracking, and user experience. Strong understanding of mobile performance advertising concepts such as app-install campaigns, CPI, CPA, ROAS, retention, lifetime value, post-install events, retargeting where allowed, and buyer outcome optimization. Experience or strong familiarity with mobile attribution and measurement ecosystems, including MMPs, AppsFlyer, Adjust, Singular, Firebase, SKAdNetwork, Android attribution changes, click tracking, impression tracking, and delayed/aggregated conversion signals. Strong knowledge of mobile privacy and compliance constraints, including Apple ATT, IDFA availability, Android Advertising ID, SKAdNetwork, Google Privacy Sandbox for Android, COPPA, GDPR, CCPA/CPRA, TCF, GPP, and do-not-sell/share flags. Practical knowledge of mobile supply quality and fraud prevention, including app bundle spoofing, SDK spoofing, device spoofing, geo mismatch, VPN/proxy traffic, click injection, click spam, invalid traffic, app-ads.txt, sellers.json, and SupplyChain object validation. Excellent interpersonal, written, and verbal communication skills with a collaborative mindset, strong ownership, and ability to work cross-functionally with Product, Data Science, DSP Partnerships, Publisher teams, Marketplace Quality, and SRE. Bonus Qualifications Hands-on experience with mobile monetization SDKs, client-server ad request flows, mediation logic, in-app bidding, server-side bidding, waterfalls, or unified auction systems. Contributions to open-source AdTech projects such as Prebid Mobile, RTBkit, OpenRTB tools, header bidding libraries, or mobile SDK/ad-serving frameworks. Familiarity with industry-standard ML model-serving infrastructure designed for real-time inference in high-QPS, low-latency environments. Understanding of mobile user acquisition, performance DSPs, app-install campaigns, MMP integrations, and attribution platforms. Experience working with incrementality measurement, retargeting systems, audience segmentation, cohort-based optimization, or privacy-safe targeting for mobile performance marketing. Exposure to privacy-preserving user ID solutions such as UID2.0, RampID, publisher first-party IDs, hashed identifiers where allowed, and frameworks such as SKAdNetwork for iOS post-ATT monetization. Experience with cross-format mobile monetization strategies, including combining rewarded video, interstitial, native, banner, app-open, playable, and video monetization within the same app session. Familiarity with real-time analytics pipelines used to measure mobile monetization KPIs such as bid rate, win rate, fill rate, eCPM, revenue, QPS efficiency, timeout rate, attribution feedback, buyer spend, and yield efficiency. Publications, patents, internal platform leadership, or speaking engagements in mobile monetization, AdTech infrastructure, RTB optimization, privacy-safe advertising, or ML for AdTech. Why Join Us? Work on high-scale mobile monetization infrastructure that directly impacts publisher revenue, DSP spend, and advertiser outcomes across the in-app advertising ecosystem. Help shape the future of ML-powered mobile monetization, real-time ad decisioning, traffic shaping, attribution readiness, and privacy-safe performance advertising. Build systems that improve monetization across premium mobile formats such as rewarded video, interstitial, native, banner, app-open, playable, and video ads. Collaborate with industry-leading engineers, product teams, machine learning experts, DSP partners, publisher teams, and marketplace quality teams. Competitive compensation, performance-based incentives, and strong career growth opportunities in a globally recognized AdTech company. AI-Enabled Engineering Mindset: We value engineers who actively leverage Generative AI tools and IDEs (e.g. GitHub Copilot, ChatGPT, Claude, Cursor, Windsurf etc.) to accelerate development, improve code quality, automate repetitive tasks, and enhance documentation and debugging workflows. Engineers who demonstrate AI-first thinking using these tools to drive faster experimentation, ideation, and technical execution will thrive in our high-scale, performance-critical environment. Qualifications: Should have a bachelor’s degree in engineering (CS / IT) or equivalent degree from well-known Institutes / Universities. Additional Information: Return to Office : PubMatic employees throughout the global have returned to our offices via a hybrid work schedule (3 days “in office” and 2 days “working remotely”) that is intended to maximize collaboration, innovation, and productivity among teams and across functions. Benefits : Our benefits package includes the best of what leading organizations provide, such as paternity/maternity leave, healthcare insurance, broadband reimbursement. As well, when we’re back in the office, we all benefit from a kitchen loaded with healthy snacks and drinks and catered lunches and much more! Diversity and Inclusion : PubMatic is proud to be an equal opportunity employer; we don’t just value diversity, we promote and celebrate it. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. About PubMatic PubMatic is one of the world’s leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes. Founded in 2006 with the vision that data-driven decisioning would be the future of digital advertising, we enable content creators to run a more profitable advertising business, which in turn allows them to invest back into the multi-screen and multi-format content that consumers demand.

About the Role We are hiring a Principal/Senior Software Engineer to lead the design and evolution of our high-frequency, large-scale AdTech platform. This pivotal role blends deep expertise in Java backend systems with cutting-edge Generative AI applications. You'll own complex software systems end-to-end, shape the organization's technical direction, and thrive at the intersection of extreme scale - trillions of daily transactions - and bold innovation. What You'll Do: Lead architectural vision for scalable, high-performance systems meeting strict security and maintainability standards. Create and present independent design reviews; translate feature requirements into robust technical designs with end-to-end ownership of planning, execution, and release. Propose and integrate Generative AI to optimize ad delivery, targeting, and system efficiency. Develop and maintain scalable backend services using Java, Spring Boot, RabbitMQ, Elasticsearch, and related frameworks. Design efficient data models and optimize MySQL/PostgreSQL queries for high performance and reliability at massive scale (trillions in data volume, concurrency, transactions). Implement observability with comprehensive logging, metrics, tracing, and alerting using Filebeat, ELK stack, and similar tools. Guide team on code quality, design patterns, and documentation; participate in code reviews, design discussions, and cross-team decisions. Mentor junior/senior engineers and deliver technical deep-dive training sessions every 3–4 months. Solve "impossible" problems creatively, align with organizational goals, and foster a culture of innovation and technical leadership. We'd Love for You to Have: 5 - 8 years of core software engineering experience, with a proven track record designing and deploying enterprise-grade applications. Expert Java backend skills: Advanced proficiency in Java 11+, Spring/Spring Boot ecosystem, and REST web service development. Exceptional problem-solving: Strong analytical skills to troubleshoot complex distributed systems in dynamic, high-stakes environments. Hands-on AI/GenAI experience: Building RAG (Retrieval-Augmented Generation), agentic workflows, and model integrations. Data mastery: Expertise in relational databases (MySQL, PostgreSQL)—schema design, query optimization, and performance tuning. Middleware & scaling: Practical work with messaging queues (RabbitMQ, Kafka), caching (Redis, Memcached), and high-concurrency systems. DevOps mindset: Strong understanding of CI/CD, Kubernetes, Docker, and monitoring (ELK, Prometheus/Grafana). UI exposure (good to have): AngularJS or modern Angular for frontend development. AdTech knowledge (preferred): Digital advertising, real-time bidding, or high-volume data processing. Qualification: Should have a bachelor’s degree in engineering or an equivalent degree from a well-known institute/university. Additional Information: Return to Office : PubMatic employees throughout the globe have returned to our offices via a hybrid work schedule (3 days “in office” and 2 days “working remotely”) that is intended to maximize collaboration, innovation, and productivity among teams and across functions. Benefits: Our benefits package includes the best of what leading organizations provide, such as paternity/maternity leave, healthcare insurance, broadband reimbursement. As well, when we’re back in the office, we all benefit from a kitchen loaded with healthy snacks and drinks and catered lunches and much more!. Diversity and Inclusion : PubMatic is proud to be an equal opportunity employer; we don’t just value diversity, we promote and celebrate it. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status About PubMatic PubMatic is one of the world’s leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes. Founded in 2006 with the vision that data-driven decisioning would be the future of digital advertising, we enable content creators to run a more profitable advertising business, which in turn allows them to invest back into the multi-screen and multi-format content that consumers demand.