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ServiceNow is seeking a Senior Staff Software Engineer to design, build, and operate production-grade agentic AI systems embedded across its platform. You will work on autonomous agents that reason over real enterprise data, take action across workflows, and run safely at Fortune 500 scale.
Key focus areas include:
**System Design & Architecture**: Deep hands-on understanding of building end-to-end system and database architecture that scales to enterprise data and traffic. You will own the technical direction and ensure systems meet production requirements.
**Agentic Architecture**: Design and ship multi-agent systems covering orchestration, tool use, planning loops, memory management, and failure recovery. The emphasis is on production-ready systems, not prototypes or notebooks.
**Enterprise-Grounded Reasoning**: Build agents that leverage ServiceNow's data layer—CMDB, Workflow Data Fabric, and Knowledge Graph—to make decisions with context that frontier models lack on their own.
**Trust, Safety & Governance**: Own the guardrails including observability, human-in-the-loop controls, and compliance infrastructure that make autonomous systems safe to deploy at scale.
**Retrieval & Grounding**: Work closely with the search team to ensure agents are grounded in accurate, low-latency retrieval through RAG pipelines, hybrid search, re-ranking, and evaluation.
**Model Integration & 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. Strong communication skills required for managing technical and business stakeholders.
**Requirements:**
- 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, failure recovery)—not prototypes
- Hands-on experience with automation, continuous integration, build and release management processes and practices
- Full-stack software development knowledge, with JavaScript, TypeScript, and Python as advantages
- 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, retrieval evaluation metrics)
- Track record of technical leadership: architecture ownership, code quality bar-raising, and mentoring engineers on production AI practices
