Sr Staff Software Engineer

You will design, build, and operate production-grade agentic AI systems embedded across ServiceNow's platform — autonomous agents that reason over real enterprise data, take action across workflows, and run safely at Fortune 500 scale. 

Your core focus areas: 

• System designs. Hands-on and deep understanding of building end to end system and DB architecture that scale to enterprise data and traffic. 

• Agentic architecture. Design and ship multi-agent systems — orchestration, tool use, planning loops, memory, and failure recovery — that operate reliably in production, not in notebooks. 

• Enterprise-grounded reasoning. Build agents that leverage ServiceNow's data layer — CMDB, Workflow Data Fabric, and Knowledge Graph — to make decisions with context no frontier model has on its own. 

• Trust, safety, and governance. Own the guardrails: observability, human-in-the-loop controls, and compliance infrastructure that make autonomous systems safe to deploy at scale. 

• Retrieval and grounding. Work closely with our search team to ensure agents are grounded in accurate, low-latency retrieval — RAG pipelines, hybrid search, re-ranking, and evaluation — as a critical dependency of agentic quality. 

• Model integration and evaluation. Integrate frontier models (Anthropic, Google, OpenAI) into the Sense → Decide → Act → Govern architecture; evaluate trade-offs across cost, latency, and capability for production use cases. 

• Engineering leadership. Raise the technical bar through architecture decisions, code reviews, and coaching — particularly on agentic design patterns and production AI discipline.

• Communication Skill. Strong in articulation, building interpersonal skills, and managing technical as well as business stakeholders 

• 12-15 years of software engineering with strong fundamentals in data structures, algorithms, and distributed systems. 

• Hands-on depth designing, shipping, and operating agentic systems in production — multi-agent orchestration, tool calling, planning loops, memory, and failure recovery. Not prototypes. 

• Hands-on experience automation, continuous integration, build and release management processes and practices. 
• Full stack software development stack hands-on knowledge, specially JavaScript, TypeScript, Python will be added advantage 

• Working experience with frontier AI SDKs (Anthropic, Google, or OpenAI) — prompt engineering, structured outputs, and model evaluation in production settings. 

• Familiarity with RAG and retrieval patterns in production — vector stores, hybrid search, and retrieval evaluation metrics. 

• Track record of technical leadership: architecture ownership, code quality bar-raising, and mentoring engineers on production AI practices.