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Staff Software Engineer (Federal)

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Hybrid

Staff Software Engineer (Federal)

ServiceNow

Staff Software Engineer (Federal)

Skills

Google Cloud PlatformPythonProduct ManagementJavaMicroservicesSpring BootMachine LearningAIAWSKubernetesFastAPIServiceNowComplianceJavascriptAzure

19 days ago

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Important information


Contract type:

Permanent

Salary:

$176,100 – $308,200 / year

Location:

United States

Work mode:

Hybrid

Published on:

8 October 2026

What they need


  • As a Staff Software Engineer, you will independently lead the design, development, and delivery of complex, high-impact AI-native and cloud-native systems. The IC4 engineer takes ownership of critical components or features, sets technical direction within their domain, and serves as a technical resource to peers and junior engineers
  • They combine deep software engineering fundamentals with hands-on expertise in AI/ML integration, cloud architecture, and production systems. This role requires the ability to balance technical depth with organizational impact, working across teams to solve ambiguous problems and drive platform improvements
  • Lead the design and architecture of complex, production-critical AI-native systems, including LLM integrations, agentic workflows, retrieval pipelines, and inference services
  • Own end-to-end delivery of medium-to-large features or systems, including specification, design, implementation, testing, deployment, and production monitoring
  • Make informed architectural and technical trade-off decisions between latency, cost, scalability, reliability, and model quality
  • Establish evaluation frameworks, testing strategies, and production monitoring for AI-driven features; drive adoption of eval-driven development practices
  • Design and optimize high-performance data pipelines, embedding systems, and vector stores handling millions of rows and complex retrieval scenarios
  • Champion security best practices, including prompt-injection defense, data privacy, PII handling, responsible AI guardrails, and compliance with regulatory requirements
  • Participate in architectural reviews across teams and contribute to platform-level technical decisions
  • Stay current with emerging AI/ML frameworks, services, and techniques; evaluate and recommend adoption where applicable
  • Mentor junior and mid-level engineers (IC2/IC3) through pair programming, design reviews, architecture discussions, and hands-on coaching
  • Conduct thorough code reviews, including evaluation of prompts, agent logic, retrieval strategies, and AI/model behavior validation
  • Identify technical debt and improvement opportunities; advocate for and lead initiatives to address them
  • Share knowledge through documentation, brown-bag sessions, and architectural guidance
  • Contribute to hiring and interview processes; provide technical assessment and feedback on engineering candidates
  • Model best practices in software craftsmanship, testing discipline, and debugging methodology
  • Support onboarding of new team members and ensure knowledge transfer across projects
  • Work closely with product management, domain specialists, and other engineering teams to define requirements and technical specifications
  • Translate complex technical concepts and AI trade-offs for non-technical stakeholders (product, leadership, customers)
  • Lead root cause analysis for customer-reported issues, including those involving model behavior, hallucinations, retrieval quality, and distributed system complexity
  • Participate in design reviews, technical planning sessions, and retrospectives; contribute perspectives on technical feasibility and risk
  • Communicate clearly about design decisions, implementation challenges, AI limitations, and production incidents
  • Build and maintain relationships with adjacent teams and external partners where applicable
  • Proactively identify opportunities to improve development processes, tooling, and team efficiency
  • Develop robust, maintainable, and well-tested AI-native software using Python, Java, and JavaScript as appropriate
  • Build comprehensive unit tests, integration tests, and AI evaluation harnesses (accuracy, regression, hallucination detection)
  • Troubleshoot complex issues in distributed systems, probabilistic models, and cloud infrastructure; isolate root causes efficiently
  • Implement secure coding practices and responsible AI guardrails throughout the development lifecycle
  • Manage deployment, monitoring, and iteration of features in production; respond to performance issues and model drift
  • Work with cloud services (AWS/GCP/Azure), managed AI services (Bedrock, Vertex AI, Azure OpenAI), Kubernetes, and CI/CD pipelines
  • Contribute to code and architecture standards; ensure adherence to established best practices
  • Design and develop custom applications, extensions, and integrations on the ServiceNow platform
  • Develop workflows, business rules, and automation using ServiceNow scripting (JavaScript, GlideScript, REST APIs)
  • Build data models, forms, and dashboards for ServiceNow applications; optimize database queries for performance
  • Integrate third-party AI/ML services and custom APIs with ServiceNow platform services
  • Contribute to and maintain ServiceNow plugin and app architecture; follow ServiceNow best practices and coding standards
  • Participate in ServiceNow upgrades and configuration management; ensure compatibility with platform updates
  • Mentor junior engineers on ServiceNow platform capabilities and development patterns
  • Participate in customer issue triage and root cause analysis for production ServiceNow application issues
  • Work closely with customer success and support teams to understand and resolve complex technical issues
  • Provide technical guidance to customers on application usage, configuration, and troubleshooting
  • Identify patterns in customer issues and drive improvements to prevent recurrence
  • Contribute to customer documentation and internal knowledge bases
  • Support customer escalations; provide timely resolutions to critical issues affecting customer operations
  • Gather customer feedback and communicate product improvement opportunities back to product management

Benefits

  • Generous family leave
  • Matched donations
  • Annual learning stipends
  • Flexible PTO
  • Competitive retirement plan
  • Paid volunteer time- Experience with cloud computing platforms and managed AI services (AWS, GCP, Azure); hands-on experience with infrastructure-as-code
  • 2+ years of hands-on experience developing applications and extensions on the ServiceNow platform
  • Strong proficiency in JavaScript/GlideScript, Python, and Java; familiarity with ServiceNow scripting patterns and APIs
  • Solid understanding of ServiceNow data model, form/workflow design, and business process automation
  • Demonstrated expertise in LLM orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel) and vector databases (Pinecone, Weaviate, pgvector, etc.)
  • Strong communication skills; ability to explain technical concepts to both technical and non-technical audiences; customer-facing experience a plus
  • Track record of taking ownership of significant technical initiatives and delivering them successfully
  • 8+ years of software development experience with a Bachelor’s degree; OR 6+ years with a Master’s degree; OR 3+ years with a PhD; OR equivalent work experience
  • Practical software development experience, with 5+ years working with modern cloud-native and AI-native systems
  • Demonstrated mentorship of junior engineers or technical leadership in previous roles
  • Experience designing and optimizing high-performance data pipelines, embedding systems, and vector stores at scale
  • 3+ years of demonstrated experience integrating third-party AI/ML services and platform APIs (OpenAI, Anthropic, AWS Bedrock, Google Vertex AI, etc.)
  • Experience developing and debugging evaluation harnesses, benchmarks, and metrics for AI/ML features
  • Proven ability to troubleshoot and isolate root causes in complex, distributed, and probabilistic systems
  • Demonstrated ability to engage with customers, understand their needs, and support issue resolution
  • Solid understanding of microservices architecture, REST/streaming APIs, and modern backend frameworks (Spring Boot, FastAPI, etc.)
  • 3+ years of hands-on experience with LLM prompt engineering, agent design, and retrieval systems (RAG, semantic search, knowledge bases)
  • Proficiency with Kubernetes, containerization, CI/CD pipelines, and automated testing frameworks
  • Experience with Agile and Scrum development methodologies; comfort with iterative development and continuous improvement- This position will include supporting our US Regulated Markets
  • “This position requires passing a ServiceNow background screening, USFedPASS (US Federal Personnel Authorization Screening Standards). This includes a credit check, criminal/misdemeanor check and taking a drug test. Any employment is contingent upon passing the screening. Due to Federal requirements, only US citizens, US naturalized citizens or US Permanent Residents, holding a green card, will be considered

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