Careers at ServiceNow

About the Cloud Hardware Engineering Team The Cloud Hardware Engineering Team works with some of the most innovative and advanced technologies in the business. We are a highly collaborative and inclusive team where individuals with strong technical aptitude, deep industry expertise, and a collaborative attitude have the opportunity to grow their professional careers and mentor peers as they work across the organization. We provide competitive compensation, generous benefits, and a professional, innovation-focused work atmosphere. About the role As a Sr Staff Cloud Architect, you will directly lead enterprise-scale cloud architecture initiatives that shape ServiceNow's infrastructure across private, sovereign, and public cloud environments. Your architectures will ensure optimal performance, security, and cost efficiency across our global cloud footprint. This is a critical role requiring deep expertise across multiple technical domains. You will serve as a force multiplier, leveraging specialized knowledge in public cloud offerings, database performance, Linux kernel tuning, and modern CPU architectures to solve complex problems affecting our entire customer base from high-value enterprise accounts to new cloud deployments. The solutions you architect will power ServiceNow's platform including large-scale application and database deployments to specialty services like customer analytics, fleet telemetry, and AI workloads. What you get to do in this role: Architect enterprise-scale solutions spanning private datacenters, sovereign cloud, and public cloud platforms (AWS, Azure, GCP). Evaluate and benchmark emerging technologies, services, and architectural patterns prior to production adoption. Drive hardware enhancements from original concept through final implementation across all system architectures and assess impact of design decisions on performance, security, and capacity. Evaluate and test new products, frequently prior to general availability. You will help automate evaluations, determine issues with designs, help identify root cause issues, and drive vendors internal and external to resolve issues. Work closely with engineering and infrastructure teams across the organization to understand the impacts of new software platform enhancements on the private and public cloud stack. Lead research and development efforts to identify emerging cloud, hardware, and software technologies, architectures, and designs with hands-on opportunities to benchmark, validate, and determine viability for future system designs. Serve as top-tier escalation for complex issues. Conduct cross-domain root cause analysis for complex infrastructure issues, coordinating investigations across database, OS, networking, and hardware layers. To be successful in this role you have: Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry. 12 years of related experience with a Bachelor's degree in Computer Information Systems (CIS), Management Information Systems (MIS), Computer Science (CS), Computer Engineering (CE), Electrical Engineering (EE), or related field; or 8 years and a Master's degree; or a PhD with 5 years experience; or equivalent experience. 10+ years evaluating, cost-modeling and implementing new datacenter technologies, including managing multi-vendor RFPs. 10+ years profiling and evaluating Linux and database performance. 7+ years hands-on with AWS, Azure, or GCP (compute, storage, networking, managed databases, cost optimization) 3+ years with Kubernetes and containerized infrastructure at production scale. Proven ability to lead complex transformation initiatives across multiple organization units. Thought leader and mentor with proven force-multiplier impact. Excellent communication and customer skills, conflict management, and interpersonal skills. Must be able to communicate at a level appropriate to the audience. For positions in this location, we offer a base pay of $190,900 - $334,100 , plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

What you get to do in this role: Design, build, and operate cloud-native engineering platforms for software validation, release validation, and production readiness Design and maintain production-like release and test ServiceNow environments that improve release confidence and deployment readiness. Build and integrate automated test pipelines, observability, reliability signals, deployment intelligence, and quality gates into CI/CD workflows. Develop automation solutions that improve engineering productivity, streamline operations, and reduce manual toil through shift-left engineering practices. Build reusable frameworks, self-service engineering environments, test data management, mock services, and developer productivity tooling. Design and enhance Kubernetes-based platforms supporting scalable test infrastructure, release automation, cloud-native workloads, and developer self-service. Implement automated validation for failure detection, deployment verification, policy enforcement, security checks, resilience testing, and operational health assessments. Resolve complex platforms, infrastructure, and networking challenges through software engineering, systems design, and automation. Partner closely with engineering teams to improve platform reliability, release quality, cloud-native adoption, and engineering best practices. Participate in architecture reviews, technical design discussions, and implementation of scalable, automation-first engineering solutions. Influence technical decisions through strong engineering execution, collaboration, and delivery of high-quality platform capabilities. Mentor engineers through technical guidance, code reviews, knowledge sharing, and engineering best practices. Foster a culture of reliability, automation, operational excellence, continuous improvement, and customer-focused engineering. Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry. 8+ years of experience in Site Reliability Engineering (SRE), DevOps, Platform Engineering, Software Engineering, or Infrastructure Engineering with a Bachelor's degree; or 6 years and a Master's degree; or a PhD with 3 years experience; or equivalent experience. Hands-on experience with Kubernetes across cluster operations, networking, storage, security, autoscaling, and multi-cluster environments. Experience building and operating cloud-native platforms supporting scalable, highly available services. Experience integrating Kubernetes with CI/CD, GitOps, automated test pipelines, deployment validation, and cloud-native deployment workflows. Experience designing and implementing automation to improve developer productivity, release quality, and operational efficiency. Experience with progressive delivery practices, including canary deployments, feature flags, automated rollback, and deployment verification. Experience with chaos engineering, resilience testing, disaster recovery, and reliability validation. Strong software engineering skills with hands-on experience designing, developing, testing, and debugging applications using Python, Go, Java, or Ruby. Experience leveraging AI-assisted engineering for intelligent testing, release risk analysis, incident diagnostics, or operational automation is a plus. Strong understanding of observability, monitoring, SLI/SLOs, incident management, and production operations for distributed systems. Demonstrated ability to solve complex technical problems, drive projects independently, and collaborate effectively across engineering teams. Thrives in fast-paced, ambiguous environments with a strong ownership mindset, bias for action, and a passion for continuous learning and automation. Low ego, intellectually curious, and an effective collaborator who enjoys partnering with globally distributed teams to deliver reliable engineering solutions. Good to have: Experience with observability and monitoring platforms for applications, services, and distributed systems at scale. Experience with DevOps automation, CI/CD pipelines, GitOps, and Agile development practices using tools such as GitLab CI/CD, Argo CD, or Flux. Experience building and maintaining enterprise-scale test automation frameworks using technologies such as Playwright, Selenium, Cypress, REST Assured, PyTest, JUnit/TestNG, or equivalent. Experience with test orchestration, intelligent regression testing, test impact analysis, flaky test detection, parallel execution, and test data management. Experience with service virtualization, contract testing, synthetic testing, and building developer self-service engineering platforms. Experience with Infrastructure as Code and configuration management tools such as Ansible, Terraform, or equivalent. Experience with the Kubernetes ecosystem, including Helm, Argo Workflows, Kustomize, Istio/Linkerd, Gateway API/Ingress, Prometheus, OpenTelemetry, and container runtime technologies. Experience operating Kubernetes platforms across public cloud providers, including AWS (EKS), Azure (AKS), and Google Cloud (GKE). Experience implementing progressive delivery practices, including canary deployments, feature flags, deployment verification, and automated rollback. Familiarity with AI-assisted engineering, intelligent testing, operational automation, or cloud-native engineering platforms. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

We are building AI-enabled product capabilities that improve through data, feedback, and real-world use. We need the production systems that make those capabilities dependable: repeatable delivery, measurable quality, controlled learning loops, and reliable operation at scale. We’re looking for a hands-on Staff Engineer who can move machine-learning models, agentic workflows, and self-learning approaches from promising prototypes into secure, observable, continuously deployable production systems. This role sits at the intersection of ML systems, platform engineering, and site reliability engineering. You will partner with ML, data, product, and infrastructure teams to create a paved path from experimentation to production—and take ownership of how those systems perform and evolve once deployed. What you’ll do Design and build the production path for the complete ML lifecycle: data and feature preparation, training, experiment tracking, evaluation, artifact and model management, serving, monitoring, feedback collection, and retraining. Build continuous-delivery workflows for models, prompts, agent workflows, data dependencies, and supporting services. Establish automated quality, safety, performance, and compatibility checks. Implement safe rollout patterns such as shadow traffic, canaries, progressive delivery, feature flags, versioned artifacts, automated rollback, and operational kill switches. Turn self-learning approaches into controlled production feedback loops. Build systems for collecting outcomes, validating feedback, maintaining lineage, triggering model refreshes, comparing candidates, and promoting changes under explicit guardrails. Define and operate SLIs, SLOs, alerts, and error budgets across infrastructure, data pipelines, inference services, model quality, and product behavior. Connect model analytics and product telemetry with traditional operational signals so teams can understand whether a problem originates in infrastructure, data, model behavior, or the surrounding product. Improve the scalability, availability, latency, and cost efficiency of distributed training, inference, and data-processing workloads. Own capacity planning and resource optimization, including GPU resources where applicable. Participate in production ownership across the service lifecycle: architecture reviews, deployment, on-call, incident response, blameless postmortems, and systemic remediation. Build self-service platforms and automation that reduce operational toil and shorten the time required for ML engineers and data scientists to reach production. Apply LLMs or agentic automation to evaluation, troubleshooting, and operational workflows where they produce reliable, measurable improvements. Establish practical standards for cloud infrastructure, Kubernetes, infrastructure as code, observability, security, and compliance. Provide technical leadership across ML, data, product, and platform teams, mentoring engineers and influencing architecture without relying on formal authority. To be successful in this role you have: A track record of Staff-level technical ownership, typically gained through 7+ years of experience in software engineering, platform engineering, SRE, production engineering, or ML infrastructure. Strong software-engineering skills in Python and at least one production systems language such as Go, Java, C++, or Rust. Experience designing, operating, and troubleshooting distributed production systems, including failure analysis, capacity planning, and performance optimization. Hands-on experience with cloud infrastructure, containers and Kubernetes, infrastructure as code, CI/CD, and modern observability. Practical understanding of the ML lifecycle—including training, evaluation, model deployment, serving, monitoring, versioning, and retraining—and the ability to collaborate effectively with applied ML engineers or researchers. Experience distinguishing service-health problems from data-quality or model-quality problems. Familiarity with SRE practices such as SLIs/SLOs, error budgets, sustainable on-call, incident management, and blameless postmortems. A strong automation and internal-customer mindset: you build platforms that are reliable, understandable, and pleasant for other engineers to use. Excellent technical judgment and communication skills, especially when navigating ambiguity and coordinating across teams during production incidents. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

About the opportunity We are seeking a passionate Senior Software Engineer to play a critical role in designing, developing, and maintaining the cutting-edge technology that powers Veza. In this role, you will work closely with cross-functional teams to build robust, scalable, and secure solutions that meet the evolving needs of our customers. This is an exciting opportunity to make a significant impact in a high-growth startup and contribute to its continued success. You will: Design, develop, and maintain backend services, ensuring high performance, scalability, and reliability. Collaborate with product managers, other software engineers, UX Designers and security experts to build product features that meet business objectives and security standards. Implement logging, monitoring, and auditing capabilities to ensure visibility and compliance with regulatory requirements. Continuously optimize and improve the performance, security, and scalability of the platform through code reviews, testing, and refactoring. Stay current with industry trends and emerging technologies and leverage them to drive innovation and improve our platform. 5+ years of developer experience Strong experience in backend programming languages (e.g., Java, Go, C++, Rust, Python, or similar). Background in enterprise-grade distributed systems Strong understanding and experience with AI development tools A deep understanding of good software design principles combined with a practical mindset. Excellent problem-solving skills, ability to work independently and collaboratively in a fast-paced environment and deliver high-quality solutions efficiently. Strong communication and interpersonal skills Self-driven and hands-on developers who enjoy writing code, solving problems, and building systems—more doers than talkers. Proven experience in designing and implementing RESTful APIs and microservices architectures. Background in IGA industry is a big plus Solid understanding of database(e.g., relational db) and caching mechanisms Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

We are the AI Experience Framework (AIUX) team that builds the platform that powers ServiceNow's AI-first user interfaces. Using modern Lit-based web components, AIUX builds modular, reusable conversational experiences that serve as the technical foundation for conversation-first applications like Employee Slate. This role owns full-stack architectural decisions in a modern JavaScript/component-driven environment, working across AI integration, performance scale, and multi-team coordination — spanning our SSR runtime (server-rendered Lit components, versioned request routing, isolated execution pools) and the ServiceNow Glide platform layer it integrates with. What you'll do: Work with product owners to understand detailed requirements and drive the full development lifecycle Build software that is simple to use, allowing customers to extend and customize functionality to meet their specific needs Contribute to the design and implementation of new products and features while enhancing the existing product suite Apply advanced knowledge of data structures, algorithms, OO design, design patterns, and performance/scale considerations Raise the engineering bar through architecture reviews, code reviews, mentoring, and technical direction To be successful in this role you have: Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry. Completed a Master's degree in Computer Science, Computer Engineering, or similar field 3 years of professional software engineering experience with deep expertise in JavaScript and substantial experience in Java or a similar OO language (C++, C#, Go) Passion for JavaScript and the Web as a platform, reusability, and componentization Strong and demonstrated experience with modern UI frameworks: Angular, React, Vue, or Lit Strong and demonstrated knowledge of data structures, algorithms, object-oriented design, design patterns, and performance/scale considerations Strong and demonstrated knowledge and experience with relational databases: development, troubleshooting, and performance optimization Strong and demonstrated experience in server-side rendering and hydration, including the failure modes specific to isomorphic rendering (markup mismatches, browser-API leakage into server code) Strong and demonstrated systems-level Node.js experience: process/worker isolation (V8 isolates or equivalent sandboxing), HTTP/1.1 and HTTP/2 semantics, reverse proxying, and designing for concurrent versioned rollouts Comfortable working across a JVM/Maven backend (Java, ServiceNow Glide platform conventions) in addition to a Node/TypeScript SSR stack Demonstrated experience as a senior individual contributor responsible for code quality, and mentoring Exposure to multiple technology stacks: Cloud Dev, Platforms, Web Dev, Frameworks, service-oriented architecture Preferred — AIUX Framework specific Experience with build systems that emit multiple targets from one component source (server bundles vs. code-split browser bundles) Hands-on experience operating services in Kubernetes: deployment configuration, scaling, rollout/rollback, and incident response Experience building and maintaining observability tooling (Grafana dashboards, Prometheus alerting) for production systems For positions in this location, we offer a base pay of $130,000 - $145,000 , plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

About the role We are hiring a staff software engineer (IC4) for the Telemetry Data Platform team, which carries product usage telemetry for the entire ServiceNow platform on a stack built with Kubernetes, Kafka, and ClickHouse. We are distributed across Israel, India, and the Americas. This is a full stack role with its center of gravity firmly on the infrastructure side — expect roughly two-thirds of your time on telemetry infrastructure, data pipelines, Kubernetes and DevOps work, and the rest on the services and product surfaces on top. You will be equally comfortable designing a distributed system and owning it in production. If you like following a system from the event that fires to the chart that renders — and you want the pager for it — you will feel at home. You will lead design and delivery of complex, multi-service features, own technical decisions within a domain, and are fully self-directed — escalating only genuine ambiguities and driving decisions to closure. Of the ten critical skills at this level, incident response management is the only one set at Expert; the rest are Experienced. What you’ll do Telemetry infrastructure and data pipelines Design, build, and own backend services for distributed data streaming and processing that handle high-volume, high-cardinality event data with predictable latency and no silent data loss. Build and maintain Kafka-based streaming pipelines and the pipeline components that feed ClickHouse. Own data modeling and query performance in ClickHouse — partitioning, sort keys, materialized views, retention, and the cost curve that comes with all of it. Partner with product and platform teams to shape requirements for telemetry ingestion and processing, then drive the solutions to production. Kubernetes, DevOps, and production ownership Deploy, scale, and operate services in production Kubernetes environments, including Helm-based deployments and CI/CD pipelines that make releases repeatable and safe to roll back. Own observability for what you build — meaningful metrics, useful logs, real tracing, and alerts that fire on customer impact rather than on noise. Debug and resolve production incidents independently, participate in on-call, run root-cause analysis, and operate against defined service level objectives. Full stack engineering and technical leadership Own the full development lifecycle for your work, and build the backend services and APIs that expose telemetry to internal consumers, product surfaces, and AI agents — including API contracts, data models, and schema migrations. Contribute to the analytics front end — dashboards, funnels, and exploration tools — with an eye on performance against large result sets, and improve the web and mobile capture SDKs. Lead the design of complex, multi-service features across team boundaries, drive decisions to closure, and write the design docs and postmortems that outlive the conversation. Raise the bar through code review, test strategy, and automation coverage, and mentor engineers on the team. Experience and education requirements The job profile defines IC4 by scope, independence, and impact rather than years served. The minimums below are the screening bar for this requisition. Requirement Mandatory minimum 8+ years of Backend software engineering experience 4+ years of Designing and operating distributed systems 3+ years Kubernetes in production, including Helm and CI/CD 3+ years Kafka or equivalent streaming and data pipelines 3+ years On-call and production ownership Bachelor’s degree in computer science, software engineering, or a closely related technical field Required A master’s degree may offset up to one year of the experience minimum. Equivalent practical experience is considered where technical depth is clearly demonstrable. Required qualifications Strong backend development experience in Java, Python, Go or equivalent, used in production at scale. Hands-on experience building distributed systems for data streaming, processing, and storage. Production experience deploying and managing services on Kubernetes, including Helm and CI/CD pipelines. Working knowledge of Kafka or an equivalent messaging and streaming system. Solid SQL skills and hands-on experience with a columnar or analytical data store, including query optimization and physical data modeling. Demonstrated depth in incident responseand customer escalations Enough front-end capability to build and debug a data-heavy interface: JavaScript or TypeScript with React or Angular. Desired qualifications Production experience with ClickHouse or another OLAP or columnar store — sharding, replication, materialized views, cost tuning. Exposure to observability tooling: OpenTelemetry, metrics and logging stacks, alerting platforms. Experience building product analytics or telemetry platforms, or with stream processing frameworks such as Flink or Spark. Client-side instrumentation — web or mobile SDK development, event capture, session and consent handling. AI skills Artificial intelligence strategy is a critical skill at Experienced proficiency for IC4 — it applies to how you build and to what you build. Confident use of AI coding assistants such as GitHub Copilot or Cursor, paired with the critical eye to review AI-generated code as rigorously as any other — catching logic errors, security anti-patterns, and missed edge cases rather than treating model output as production-ready. AI-assisted debugging and trace analysis, and a clear understanding of the data privacy rules governing what goes into a prompt. Integrating LLM APIs into production features — and knowing when a model is the wrong tool for the job. Working knowledge of RAG pipelines, embedding stores, and agent frameworks; familiarity with the Model Context Protocol is a plus. Exposing telemetry to AI agents through tool interfaces agents can use safely: predictable schemas, bounded results, clear error semantics, sane cost controls. Designing safeguards for non-deterministic components — retry logic, circuit breakers, human-in-the-loop checkpoints — and hardening against latency spikes and hallucinated output reaching a customer. Instrumenting AI features in production and judging their quality from telemetry and evaluation rather than impressions. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

About the team The Security and Risk Engineering organization builds scalable, AI-powered security solutions that reduce risk and protect ServiceNow and its customers. We value AI-first thinking, clean architecture, intuitive experiences, and a culture of continuous learning. This is a zero-to-one incubation. We’re building a new class of exposure analysis that ranks security work by exploitability—where an attacker could realistically get in—rather than raw severity. The architecture is evolving, and this role helps define what good looks like. The role As a Senior ML Engineer, you build core components of a novel exploitability engine—shipping production ML that turns raw security signal into ranked, reachable attack paths. You take well-scoped problems from design to production and grow into deeper ownership as the system matures. What you’ll own Well-scoped components of the engine—evidence ingestion and connectors, entity resolution, graph construction, or parts of the probability core—built to production quality. The correctness and reliability of what you ship: tests, evaluation, observability, and the metrics that show your component works. Turning ambiguous requirements into working code, with guidance on the calls that shape the wider system. The data and model plumbing that keeps the graph accurate—entity-resolution quality, evidence provenance, and decay. What you’ll do Design, build, test, and operate production ML components with strong engineering fundamentals. Contribute to design and code reviews, and help raise the quality bar on the team. Prototype quickly to evaluate new AI capabilities against real cybersecurity problems. Partner with product, security R&D, and SecOps to understand the problem behind the ticket. Apply AI safety, security, and guardrail practices to what you build. What you bring Solid software engineering fundamentals and experience operating production-quality software. Hands-on experience building ML- or LLM-powered applications—RAG, embeddings, agents, or probabilistic or ML-driven scoring. Experience taking a prototype to a reliable, maintainable production solution. Working knowledge of distributed systems, APIs, cloud-native development, and data or graph systems. Strong Python, and/or Java, Go, or TypeScript. Interest in security problems—vulnerability management, identity security, threat detection, or risk prioritization. Experience with AI-assisted development tools and coding agents such as Claude Code, Codex, Cursor, or Windsurf is a plus. Experience with AI evaluation, safety, or guardrails is a plus. 3+ years of software engineering experience, or equivalent practical experience. Experience designing and delivering production software systems. Experience building or integrating AI/ML-powered applications in a production or near-production environment. Modern AI experience: LLMs, RAG, embeddings, vector search, agentic workflows, model evaluation, or AI observability. Strong programming experience in Python and/or Java, Go, or a similar language. Cloud-native technologies, distributed systems, APIs, databases, and scalable architectures. Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline, or equivalent practical experience. Cybersecurity or security-product experience is a plus. For positions in this location, we offer a base pay of $143,200 - $243,400 , plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

Software Engineer, Fullstack As a Fullstack Engineer on the web team, you will play a lead role in creating the next generation of the Moveworks Agentic Assistant ecosystem. The ability to leverage ML and Generative AI intelligence for the fullstack makes it innovative and fun! Join us, and you'll find yourself in a unique playground, working on web applications that directly impact every Moveworks customer. In other words, we needed you here yesterday! We're crafting an enterprise-focused GAI ecosystem. You'll shape diverse functionalities, cater to various user personas, and forge a solution that meets enterprise needs. Your role spans designing AI powered agent builder experiences and creating robust UI frameworks with scalable, reliable building blocks. What you will do: Design and implement AI powered agent builder product features using cutting-edge technical approaches to deliver business value. Expand the product's reach to more customers, domains, and global markets, ensuring high quality engineering implementation. Architect and build out Moveworks web technology stacks such as authentication, event tracking, application platform, and design systems. Promote best practices and standards to build modular and scalable web apps and APIs between backend services. Work closely with the product, ML and engineering teams to augment user experience, find creative solutions to fill in gaps in technology, and increase customer adoption. Work at a startup pace in a small company with a high degree of ownership What you bring to the table: BS or higher degree in computer science or a related field, or equivalent relevant experience 5+ years of professional development experience in building complex web applications Experience with major modern Web UI framework (e.g. ReactJS) and experience building UI at scale Strong product sense and a passion for building scalable web or conversational UI products Excellent cross-functional collaboration skills A constant thirst for learning and a willingness to get out of your comfort zone Nice to Have Experience working with AI Agent products For positions in this location, we offer a base pay of $143,200 - $243,400, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.

ServiceNow seeks a Staff Application Security Engineer to serve as the technical core of our bug bounty program within the Product Security Incident Response Team (PSIRT). This is the senior engineer who owns bug bounty reports from intake through resolution: reproducing and validating the vulnerability, assessing its severity, and seeing it through to a verified fix. The work is deeply technical. Reproducing a vulnerability is only the starting point. From there you read the underlying code, identify root cause, and either propose the fix or design it alongside engineering before confirming it holds. You are also the person researchers deal with directly, which makes clear, credible communication as central to the role as the technical analysis itself. As one of the most senior engineers on the team, you will set the standard for how triage is done and mentor earlier-career engineers. Beyond the bug bounty queue, you will conduct variant hunts, perform original platform security research, lead major product security incidents, and run forensic postmortems when a significant issue reaches production. Key Responsibilities Triage and Resolve Bug Bounty Reports Own incoming reports end-to-end: intake, reproduction, severity scoring, root cause analysis, fix verification, and final disposition. Reproduce and validate reported vulnerabilities, building out incomplete proof-of-concept code where needed. Serve as the technical escalation point for the most complex and highest-severity reports, including multi-step exploit chains and cross-system issues. Perform code review and root cause analysis to identify the underlying defect rather than the reported symptom. Propose remediations, or design them with engineering, and verify the fix resolves the issue. Assign and defend severity ratings using the program's severity framework. Route issues to owning teams, file and track defects, and keep vulnerability records accurate through closure. Own Researcher and Stakeholder Communication Act as ServiceNow's primary technical point of contact for bug bounty researchers across the full lifecycle of a report. Handle severity and validity disputes directly, keeping every exchange clear, timely, respectful, and technically credible. Translate technical findings for internal stakeholders and keep engineering and leadership current on status and risk. Mentor the Team and Raise Triage Standards Provide technical mentorship to earlier-career PSIRT engineers, developing depth in reproduction, code analysis, severity judgment, and communication. Set and maintain the bar for triage quality and strengthen program practices over time. Lead Advanced Security Work Beyond Triage Conduct variant hunts to find related instances of reported vulnerabilities before they are discovered externally. Perform original platform security research to surface issues ahead of external researchers. Lead major product security incidents on the PSIRT side, coordinating response across teams under pressure. Run forensic postmortems after significant incidents to determine how the issue reached production, including how design-level flaws bypassed release processes, and confirm that remediations hold. To be successful in this role, you have: 8+ years of hands-on experience in product security, application security, penetration testing, or vulnerability research. Depth of expertise matters more than years. Expertise in: Common web and application vulnerability classes and exploitation techniques. Vulnerability reproduction, severity assessment, and defensible risk scoring under ambiguity. Coordinated vulnerability disclosure. Code and development fluency: Strong code comprehension in Java, JavaScript, and Python, with the ability to trace root cause in large, unfamiliar codebases and review pull requests. Ability to write code and propose concrete fixes. This is not an application-building role, but you reason fluently in code. Working knowledge of Git, Gradle, Maven, CI/CD pipelines, and secure SDLC. Proficiency with Claude Code or equivalent AI coding assistant for code comprehension and security research. Exceptional written communication. You will represent ServiceNow directly to external researchers, frequently in disagreement, and bridge those researchers and internal engineering. This is a core requirement of the role, not a supporting skill. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

Role summary The Staff Software Engineer (IC4) on Sales and Order Management designs, builds, ships, and operates capabilities whose core behavior is model-driven rather than explicitly authored—agentic and conversational experiences that interpret a seller's or customer's intent, reason over catalog, quote, and order context, invoke tools, and act on the user's behalf across the quote-to-order lifecycle. This is not a machine learning or AI research role; the engineer does not train foundation models. It is also distinct from traditional full-stack engineering, where systems follow deterministic logic rather than selecting execution paths at runtime. Two consequences shape the work. First, the most important logic often lives in natural language—instructions, prompts, tool descriptions, guardrails, escalation rules—which must be engineered, versioned, and reviewed with the same discipline as code. Second, because behavior is probabilistic, correctness is established by measuring behavior at scale rather than by asserting fixed outputs, making automated evaluation a first-class engineering activity rather than a quality-assurance afterthought. The stakes in this domain sharpen both points. An agent operating on quotes and orders touches pricing integrity, contractual commitment, and revenue recognition—a confidently wrong output is not a bad answer, it is a mispriced order. At IC4 the engineer owns AI design decisions across the domain, not within a single feature, and owns the correctness of what ships whether a person or an agent produced it. What you do Build AI-native capability across the order lifecycle Design and ship features built around agentic behavior—intent interpretation, multi-step reasoning, tool invocation, and action on the user's behalf—together with the data models, integrations, and channels that make them usable in production. In Order Management this spans guided offer selection and configuration, natural-language order construction and validation, conversational order status and in-flight change, order-exception triage and resolution, and promise-date and availability inquiry. Design AI-driven autonomous workflows Decompose sales and order processes into the steps and decision points an agent can execute—determining where autonomy is appropriate, where a checkpoint with a person is required, and how exceptions, retries, and hand-back are handled. The design must make that distinction structural rather than advisory. Author and maintain agentic instructions as engineering artifacts Write, structure, and version the system instructions, role definitions, tool descriptions, guardrails, and escalation paths that govern agent behavior in the domain—under code review, source control, and regression coverage. Own the shared instruction and tool-description surface that adjacent teams build against. Build automated evaluation and test non-deterministic behavior Design and operate the evaluation that makes change safe — golden datasets, multi-turn conversation suites, model-as-judge scoring calibrated to human review, CI gates, and drift detection — plus adversarial, jailbreak, grounding, and tool-selection testing. Design conversational experiences across channels Build experiences that hold context across turns, hand off cleanly between automated and live agents, and behave consistently across chat and voice—accounting for what voice imposes: latency budgets, barge-in, speech recognition error, disambiguation, and explicit confirmation before consequential actions. Specify precisely and direct AI coding agents Convert requirements into testable specifications with explicit scope, constraints, non-goals, and acceptance criteria; decompose work into agent-sized tasks; supervise several workstreams in parallel; and review agent output for correctness, spec adherence, security, and maintainability. You own the result regardless of what produced it. Own quality, safety, and reliability in production Monitor conversation quality, containment, hallucination rate, tool-selection error, and unsafe or unauthorized action. Defend against prompt injection and data leakage across integration surfaces. Maintain reasoning-trace observability and model rollback mechanisms, and feed production failures back into specifications and evaluation sets. Lead root-cause analysis when agentic behavior deviates from intent. Ground it in solid full-stack delivery Build the application, APIs, data models, and integrations around these capabilities—front-end experiences for sellers and order agents, server-side logic, and the connections to quoting, billing, contract, case, and fulfillment systems—with the CI/CD, observability, and upgrade-safe extensibility expected of production software. Collaborate across product, design, and engineering Partner with product managers, designers, conversation designers, and engineers to define success criteria and communicate capability and risk clearly. Mentor IC1 to IC3 engineers, and raise the team's practices around instruction authoring, evaluation, and accountable agent use. Required experience and skills Production track record. A demonstrated record of building, shipping, and operating production software, including hands-on delivery of AI-native application features that real users depend on rather than demos or prototypes. Depth and demonstrated judgment matter more than tenure; typically around 8+ years of relevant software engineering experience. Agentic delivery experience. Direct experience authoring agentic instructions and prompts, designing AI-driven autonomous workflows, and building the evaluation and testing that verifies them. This is required, not preferred. Production AI integration. Experience integrating large language model APIs and retrieval-grounded features, including agent orchestration, tool and function calling, and structured output enforcement. Domain ownership. Demonstrated ownership of a complex domain or subsystem end-to-end, including the architectural decisions, migrations, and operational consequences. Engineering fundamentals. Strong command of data structures, algorithms, system design, APIs, data modeling, and testing. Proficiency in front-end development with a modern component framework, server-side development, relational data modeling, and REST and GraphQL API design. Applied machine learning literacy. A working command of the concepts that govern how these systems behave—evaluation, embeddings, and the probabilistic output and failure modes of modern models—sufficient to reason about, debug, and verify model-driven behavior in production. Accountable use of AI coding agents . Current, effective use of AI coding assistants and agents with evidence of accountable delivery: precise specification, critical review of generated output, and verification harnesses. Operational experience. Hands-on CI/CD, containerized workloads, and observability experience, plus direct on-call and incident-command experience with customer-facing systems. Mentorship. Demonstrated mentorship of less-experienced engineers and a record of raising quality through code review. Education . Bachelor's degree in computer science, software engineering, or a related technical field, or equivalent practical experience. Advanced degrees are a plus but not a substitute for a record of shipping reliable AI-native applications. Preferred experience Order and quoting domain depth. Quote-to-cash, configure-price-quote, product catalog modeling, or order management, at a depth sufficient to challenge a requirement rather than only implement it. Evaluation and observability tooling. Evaluation frameworks, prompt and instruction management tooling, tracing for model-driven applications, and analysis of production transcripts at scale. Conversation design partnership. Working alongside conversation or content designers on dialogue flow, tone, and error-recovery design. Forward deployed delivery. Building against a customer's data, integrations, and channels, and tuning instructions and evaluation sets in their environment. Platform and standards depth. Industry order-management interoperability models, or Now Platform development experience: scoped applications, Flow Designer, UI Builder, Automated Test Framework, and upgrade-safe extension patterns. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.