Staff Software Engineer

Full-stack engineering and leadership

• Build backend services and APIs exposing telemetry to internal consumers, product surfaces, and AI agents.
• Contribute to analytics interfaces and improve web and mobile capture SDKs.
• Lead cross-team design of complex features, write design documents and postmortems, and mentor engineers.
• Raise code review, test strategy, and automation coverage standards.

Experience and education

• At least 8 years of backend software engineering experience.
• At least 4 years of 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.
• A master’s degree may offset up to one year of the experience minimum, and equivalent practical experience may be considered.

Required qualifications

• Production-scale backend development experience in Java, Python, Go, or an equivalent language.
• Hands-on distributed systems experience for data streaming, processing, and storage.
• Solid SQL skills and experience with columnar or analytical data stores.
• Demonstrated depth in incident response and customer escalations.
• Front-end capability with JavaScript or TypeScript and React or Angular.

Desired qualifications

• Production experience with ClickHouse or another OLAP or columnar store.
• Exposure to OpenTelemetry, metrics and logging stacks, or alerting platforms.
• Experience with product analytics, telemetry platforms, Flink, or Spark.
• Experience building web or mobile SDK instrumentation and event capture.

AI skills

• Use AI coding assistants such as GitHub Copilot or Cursor while rigorously reviewing generated code.
• Apply AI-assisted debugging and trace analysis with awareness of prompt data privacy rules.
• Integrate LLM APIs into production features and understand when a model is unsuitable.
• Use RAG pipelines, embedding stores, agent frameworks, and safe telemetry interfaces for AI agents.
• Design safeguards for nondeterministic components and evaluate AI features through production telemetry.

Work personas

• ServiceNow describes flexible, remote, and required-in-office work personas assigned according to work nature and location.
• Eligibility for a work persona may be assessed using the distance between an employee’s residence and the closest ServiceNow office.

About ServiceNow