Staff Software Engineer - Infrastructure

Full-stack engineering and leadership

• Own the full development lifecycle and build backend services and APIs for internal consumers, product surfaces, and AI agents.
• Contribute to data-heavy analytics interfaces and improve web and mobile capture SDKs.
• Lead complex multi-service designs across team boundaries, drive decisions to closure, and write design documents and postmortems.
• Raise engineering standards through code review, testing, automation, and mentoring.

Experience and education

• At least 8 years of backend software engineering experience.
• At least 4 years designing and operating distributed systems.
• At least 3 years of production Kubernetes experience, including Helm and CI/CD.
• At least 3 years of Kafka or equivalent streaming and data pipeline experience.
• At least 3 years of on-call and production ownership experience.
• Bachelor's degree in computer science, software engineering, or a closely related technical field is required.
• A master's degree may offset up to one year of the experience minimum; equivalent practical experience may be considered.

Required qualifications

• Strong production-scale backend development experience in Java, Python, Go, or an equivalent language.
• Hands-on experience building distributed systems for data streaming, processing, and storage.
• Production Kubernetes experience with Helm and CI/CD pipelines.
• Working knowledge of Kafka or an equivalent messaging and streaming system.
• Solid SQL skills and experience with a columnar or analytical data store.
• Demonstrated depth in incident response and customer escalations.
• Front-end capability with JavaScript or TypeScript and React or Angular.

AI and desired skills

• Production experience with ClickHouse or another OLAP or columnar store is desired.
• Exposure to OpenTelemetry, metrics and logging stacks, and alerting platforms is desired.
• Experience with product analytics, telemetry platforms, Flink, Spark, client-side instrumentation, or SDK development is desired.
• Use AI coding assistants critically, integrate LLM APIs, and apply privacy, reliability, evaluation, and safety safeguards to AI features.
• Working knowledge of RAG pipelines, embedding stores, agent frameworks, or the Model Context Protocol is useful.

Work personas

• ServiceNow uses flexible, remote, or required-in-office work personas based on the nature of the work and assigned location.
• Eligibility may be assessed using the distance between an employee's primary residence and the closest ServiceNow office.

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