Staff Software Engineer at ServiceNow in Santa Clara, CALIFORNIA, United States

Job description

• As a Staff 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.
• What you get to do in this role:

Responsibilities

• • 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

Requirements

• 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
• 3+ years of hands-on experience with LLM prompt engineering, agent design, and retrieval systems (RAG, semantic search, knowledge bases)
• 3+ years of demonstrated experience integrating third-party AI/ML services and platform APIs (OpenAI, Anthropic, AWS Bedrock, Google Vertex AI, etc.)
• 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
• Solid understanding of microservices architecture, REST/streaming APIs, and modern backend frameworks (Spring Boot, FastAPI, etc.)
• Experience designing and optimizing high-performance data pipelines, embedding systems, and vector stores at scale
• Demonstrated expertise in LLM orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel) and vector databases (Pinecone, Weaviate, pgvector, etc.)
• Experience with cloud computing platforms and managed AI services (AWS, GCP, Azure); hands-on experience with infrastructure-as-code
• Proficiency with Kubernetes, containerization, CI/CD pipelines, and automated testing frameworks
• 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
• Strong communication skills; ability to explain technical concepts to both technical and non-technical audiences; customer-facing experience a plus
• Experience with Agile and Scrum development methodologies; comfort with iterative development and continuous improvement
• Demonstrated ability to engage with customers, understand their needs, and support issue resolution
• Track record of taking ownership of significant technical initiatives and delivering them successfully
• Demonstrated mentorship of junior engineers or technical leadership in previous roles

Skills

Preferred

• customer-facing experience a plus

Benefits

• For positions in this location, we offer a base pay of $176,100 - $308,200, 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.