S
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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