Sr Staff Software Engineer

Job description

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

Qualifications

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.