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Software Engineer - UI (On Contract) About the Role The Software Developer role is a full-stack engineering position focused on building scalable, AI-enabled product capabilities within a mature technology ecosystem. With 3 -5 years of experience, you’ll contribute to frontend development using TypeScript and Angular, backend services in Java, and collaborate across platform, data, and product teams to deliver reliable, high-quality solutions. Exposure to Python or Golang is valued, particularly for backend services, integrations, and AI-driven components. This role emphasizes production-grade AI adoption, including Agentic AI workflows. You’ll focus on applying AI where it meaningfully enhances product outcomes—improving user experience, automation, and decision intelligence—while adhering to enterprise standards around architecture, testing, and reliability. Strong communication, disciplined execution, and the ability to align AI-driven solutions with long-term product strategy are critical to success What You'll Do 3 to 5 years’ experience in development, whereas a minimum 3+ years’ experience in UI development with the Angular 15 version and above exposure is preferred. 3+ years of design patterns, modular JavaScript, ES6, front end debugging techniques, front end build processes. Experience of 6+ months in backend API development is a plus. API development using NodeJS or other popular languages like Python. Hands-on experience in advanced JavaScript and JavaScript frameworks like AngularJS and NodeJS. Design, build, and maintain high-performance, scalable backend services using NodeJS/Python in Linux/UNIX environments. Proficiency in SQL and relational databases, including complex queries, performance optimization, schema design, indexing, and stored procedures. Knowledgeable in REST API development, patterns, and design concepts using NodeJS, Python, etc. Strong knowledge of Data Structures and OOPS concepts. UI and backend codebase Unit Testing experience is a must. Problem-solving skills and the ability to learn and adopt new technologies. Experienced in working and coordinating with cross-functional teams like Product, Marketing, UX, QA, Account management, and Backend platform teams in multiple US cities and Pune, India. Knowledgeable of the performance, scalability & security considerations for web applications. A passion for developing and maintaining high-quality code and enabling contributions from engineers across the team. Leverage AI-enabled development tools (e.g., GitHub Copilot, ChatGPT, and Cursor) for coding, debugging, documentation, and automation. We'd Love for You to Have 3 - 5 years of Agile and Scrum methodologies, including sprint planning, daily stand-ups, sprint demos, sprint retrospectives, estimation, and prioritization techniques. Implementation of professional software engineering best practices for the full software development life cycle, including coding standards, code reviews, source control management, documentation, build processes, automated testing, and operations. Finding ways to increase the throughput of the team with innovation & motivation. Strong inter-personal skills and a desire to work collaboratively. Experience in handling Engineering escalations from customers will be preferred. Able to communicate clearly and effectively with all levels. Strong operational and project management skills in a product development environment. Knowledge of large-scale deployment architectures, monitoring, and CI/CD. Hands-on experience with AI-assisted coding and automation workflows. Basic understanding of prompt engineering and LLM usage for productivity. Understanding of advanced AI concepts, including RAG, agentic AI, and model fine-tuning. Qualification 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 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, and 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 Data Scientist, Performance Analytics within Engineering to build performance intelligence for our advertising platform. The role will analyze campaign and platform performance, identify anomalies and opportunities, investigate root causes, and translate data into actions for Engineering, Trading, Product, and Business. This is not primarily a reporting role—the focus is understanding what is happening, why, and what we should do about it. What You'll Do Analyze performance across campaigns, inventory, audiences, bidding, models, and conversions. Monitor and investigate CPA, CPC, CTR, VCR, ROAS, spend, delivery, and revenue. Proactively detect performance anomalies and optimization opportunities. Perform root-cause analysis across models, inventory, identity, attribution, audience, and data quality. Design and analyze A/B tests and experiments. Build reusable SQL/Python analyses, metrics, and automated diagnostics. Partner with Engineering and Trading to turn insights into measurable improvements. Convert recurring investigations into AI-assisted troubleshooting and automation. We'd Love for You to Have Strong SQL and Python skills with experience analyzing large-scale datasets. Strong analytical, statistical, and experimentation fundamentals. Experience with platforms such as Snowflake, Spark, Trino, Databricks, or BigQuery. Understanding of data pipelines, data modeling, and data quality. Strong problem-solving and communication skills. AdTech, marketplace, recommendation, or high-scale platform experience preferred. Experience with RTB, bidding, attribution, campaign optimization, or ML-driven systems is a strong plus. Qualifications: Bachelor's degree in Engineering (CS/IT) or an equivalent degree from a well-known institute or university; advanced degree is a plus but not required given depth of experience. What Success Looks Like Detect earlier → Diagnose faster → Recommend action → Automate The goal is not more dashboards. The goal is to create a performance intelligence capability that improves campaign outcomes, reduces investigation time, guides Engineering/Trading decisions, and becomes the foundation for AI-native troubleshooting. 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. 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 a Staff Software Engineer to help architect and evolve our next-generation, highly scalable, low-latency AdServer for Connected TV (CTV) – operating at a scale of 1 trillion+ requests per day and managing millions of requests per second. This is a technical leadership role for an engineer who wants to shape the architectural direction of the CTV AdServer platform, not just one team’s roadmap, in one of the fastest-growing areas of programmatic advertising. If you thrive on solving distributed-systems problems at extreme scale, enjoy influencing engineering direction across multiple teams, and want to be one of the most senior technical voices in the organization, we’d love to talk to you. What You'll Do Product & Architecture Influence: Influence multiple teams across the AdServer organization by defining and reviewing product and platform architecture and implementations. Identify architectural risks early and propose alternatives and solutions that hold up at trillion-scale. Architectural Oversight: Oversee the design and implementation of critical platform components by maintaining in-depth knowledge of best practices, technologies, architectures, and emerging technologies, and by setting the technical bar for the AdServer engineering organization. Standards & Decisions: Document and communicate exceptions to architectural standards by capturing significant architectural decisions (ADRs), ensuring decisions and their rationale are visible, durable, and reusable across teams. Own end-to-end technical direction for the AdServer platform – partnering with Principal and Senior Principal Engineers, Engineering Leads, and Product Leads to translate business needs into a coherent, multi-quarter technical roadmap. Lead the design and evolution of highly reliable, scalable, low-latency distributed backend platforms and services, and set the technical direction that other teams build on. Drive research into emerging technologies, sponsor proof-of-concepts, and make build/adopt decisions that materially move the platform forward. Act as a technical escalation point across teams – auditing designs for platform stability, reviewing major architecture changes across the AdServer Development Team, and unblocking the hardest cross-cutting problems. Partner with Data Center and DevOps teams on long-range technical planning – new technology adoption, software optimization strategy, and stability roadmaps for the overall platform. Mentor and raise the technical bar of Principal and Senior Principal Engineers, and other senior ICs, through design reviews, architecture forums, and hands-on technical guidance. Champion engineering best practices and documentation standards across teams; ensure designs meet requirements and that platform-wide work meets a consistently high quality bar. Drive the application of GenAI across the software development lifecycle – design, coding, testing, and documentation – and help set the standard for AI-enabled engineering across the org. We'd Love for You to Have 14+ years of hands-on development experience in C/C++ in a Linux/UNIX environment, with a track record of shipping and evolving large-scale distributed systems. Experience with Go is a strong plus. Demonstrated experience defining architecture and technical direction across multiple teams or a full platform, not just a single service or team. Deep proficiency in algorithms and advanced data structures, with a strong foundation in core computer science principles. Extensive experience in software design and architecture for complex, scalable, low-latency, high-throughput systems. A track record of identifying architectural risk ahead of time and driving alternatives that are adopted broadly. Ability to write and review architectural decision records, and to communicate trade-offs clearly to both engineering and product stakeholders. Excellent problem-solving skills and the ability to find optimal, innovative solutions to open-ended technical problems. Strong working knowledge of generative AI-based tools and IDEs to accelerate development; comfort with prompt engineering fundamentals and an understanding of different model types at a working level. Deep knowledge of OS internals and systems programming – multi-threading, multi-processing, and memory management – and the ability to troubleshoot the hardest production issues. Ability to write clean, modular, loosely coupled code, and to hold others to that same bar through review. Strong end-to-end understanding of product functionality across the platform, not just an individual component. Working knowledge of scripting (Perl/Python/Shell) and databases (preferably MySQL). Excellent interpersonal, written, and verbal communication skills, with experience influencing senior stakeholders and driving alignment across teams without direct authority. Good to Have - CTV Domain Experience: Prior hands-on experience building or scaling ad serving, ad decisioning, or real-time bidding systems specifically for Connected TV (CTV) / OTT. Working knowledge of CTV-specific technical protocols and standards – e.g. VAST/VPAID/VMAP, SSAI (server-side ad insertion) and CSAI, HLS/DASH manifest manipulation, and IAB CTV/OTT specifications. Understanding of the CTV supply chain and its unique constraints – device- and app-level identifiers (e.g. IFA, RIDA), frequency capping and pod/ad-break management, content-level targeting, and the latency/quality bar required for a living-room viewing experience. Familiarity with SSAI stitching architectures and the trade-offs between client-side and server-side ad insertion at scale. Exposure to OTT/streaming platforms, smart TV operating systems (e.g. Roku, Fire TV, Android TV, tvOS, Samsung Tizen, LG webOS), or set-top box environments, and the constraints they place on ad delivery. Understanding of CTV measurement, viewability, and completion-rate reporting requirements, and how they differ from traditional display/video. Awareness of the evolving CTV privacy and identity landscape (e.g. data clean rooms, alternative identifiers, cross-device graphs) and its implications for ad server architecture. 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: Bachelor's degree in Engineering (CS/IT) or an equivalent degree from a well-known institute or university; advanced degree is a plus but not required given depth of experience. 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 an experienced Engineering Manager, Data & Analytics to lead a team responsible for operating, scaling, and evolving our large-scale advertising data and analytics ecosystem. The team owns business-critical real-time and batch data systems supporting real-time reporting, scheduled reporting, ad-hoc analytics, log-level data, audiences, ad-serving use cases, observability, and machine-learning feedback loops. This role requires a strong combination of technical leadership, people management, execution, and stakeholder management. The Engineering Manager will work closely with Engineering, Product, Business, Analytics, and ML teams to evolve the existing ecosystem while maintaining reliability, scalability, performance, and cost efficiency. What You'll Do Engineering & Technical Leadership Own the technical direction and evolution of large-scale real-time and batch analytics systems. Scale streaming workloads built on technologies such as Kafka and Spark Streaming. Evolve analytical and data-processing workloads across Snowflake, HDFS, and object storage. Support real-time, scheduled, ad-hoc, and log-level reporting at advertising scale. Drive improvements in scalability, reliability, performance, data quality, and infrastructure efficiency. Modernize components of the existing ecosystem while protecting business-critical workloads. Strengthen observability, monitoring, data lineage, SLAs/SLOs, and operational excellence. Enable data capabilities supporting audiences, ad serving, experimentation, ML training and feedback loops, and AI-driven use cases. Evaluate appropriate adoption of CPU/GPU accelerated computing and emerging data and AI technologies.Drive architecture reviews and establish strong engineering standards across the team. People & Execution Leadership Lead, mentor, and grow a high-performing engineering team. Hire and develop engineers and create strong technical leaders within the organization. Establish clear ownership and accountability across critical systems. Own roadmap planning, prioritization, execution, and delivery. Balance new capabilities with technical debt, platform modernization, reliability, and operational commitments. Lead incident reviews and drive systemic fixes to prevent recurring production problems. Foster an engineering culture focused on ownership, technical excellence, simplicity, and measurable outcomes. Stakeholder Leadership Partner closely with senior stakeholders across Engineering, Product, Business, Analytics, Trading, and Machine Learning. Translate complex business requirements into scalable technical strategies. Lead challenging discussions involving priorities, timelines, technical limitations, architecture, cost, and competing business requirements. Challenge assumptions and requirements when necessary and provide data-driven alternatives. Clearly communicate technical trade-offs, risks, and investment requirements to technical and non-technical leadership. Build alignment across teams where ownership and priorities may not naturally align. We'd Love for You to Have 10+ years of engineering experience, with significant experience leading and managing engineering teams. Proven experience hiring, mentoring, developing, and growing engineers and technical leaders. Strong technical background in large-scale distributed data and analytics systems. Hands-on architectural understanding of technologies such as Kafka, Spark/Spark Streaming, Snowflake, HDFS, and object storage. Deep understanding of streaming, batch processing, distributed computing, data modeling, and analytical architectures. Experience operating and evolving high-throughput, business-critical production systems. Strong understanding of system scalability, reliability, observability, performance, and infrastructure cost optimization. Strong stakeholder management and influencing skills, including experience working with senior technical and business leaders. Demonstrated ability to navigate difficult conversations, resolve conflicting priorities, make trade-offs, and drive decisions. Ability to connect business outcomes with technical strategy and engineering execution. Experience with AdTech, high-scale real-time systems, audience platforms, ML/data infrastructure, or accelerated computing is a strong plus. Qualifications: Bachelor's degree in Engineering (CS/IT) or an equivalent degree from a well-known institute or university; advanced degree is a plus but not required given depth of experience. What Success Looks Like Success means scaling and evolving an established, business-critical data ecosystem while building a strong engineering organization around it. The platform should become more reliable, scalable, observable, cost-efficient, and easier to operate, while continuing to support growing reporting, analytics, audience, ML, and AI use cases. At the same time, the Engineering Manager should develop a team with strong technical ownership, consistently deliver against business priorities, and effectively navigate complex stakeholder discussions and competing priorities. 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. 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.