Senior Staff AI-Native Software Engineer – Agentic Systems

ServiceNow•San Francisco, CA

About The Position

The Senior Staff AI-Native Software Engineer will design, build, and operate production-grade agentic AI systems embedded across ServiceNow’s platform. These autonomous agents reason over enterprise data, act across workflows, and operate safely at Fortune 500 scale. The role is part of AI Engineering and Delivery, which builds agentic AI and enterprise-scale search systems for Now Assist, AI Agents, and other AI-driven customer experiences, with a focus on robustness, performance, safety, and customer impact. The engineer will design multi-agent architectures, including orchestration, tool use, planning loops, memory, and failure recovery; build enterprise-grounded reasoning using ServiceNow data sources such as CMDB, Workflow Data Fabric, and Knowledge Graph; and establish safety and governance controls, including observability and human-in-the-loop measures. The role also involves retrieval and grounding, integration and production evaluation of frontier models, and technical leadership through architecture decisions, code reviews, and coaching. The position works across autonomous enterprise processes, omni-channel AI resolution, and AI governance systems. The posting lists a base pay range of $190,900–$334,100 for positions in the referenced location, plus equity when applicable, variable/incentive compensation, and benefits. Compensation varies by factors including qualifications, skill level, competencies, and work location.

Requirements

8+ years of software engineering experience, with strong fundamentals in data structures, algorithms, and distributed systems.
Hands-on experience designing, shipping, and operating production agentic systems, including multi-agent orchestration, tool calling, planning loops, memory, and failure recovery.
Production-grade Python skills.
Experience with frontier AI SDKs such as Anthropic, Google, or OpenAI, including prompt engineering, structured outputs, and production model evaluation.
Familiarity with production RAG and retrieval patterns, including vector stores, hybrid search, and retrieval evaluation metrics.
A track record of technical leadership, including architecture ownership, raising code quality standards, and mentoring engineers on production AI practices.
Skills listed in the posting: React, Node.js, Python, Java, REST, GraphQL, SQL, AWS, Azure, GCP, Docker, and Kubernetes.

Nice To Haves

Experience with a systems language such as Go, Java, or C++.
Deeper specialization in search and retrieval at scale or MLOps/model observability.
Published work or open-source contributions in agentic systems or retrieval.
Exposure to LLM fine-tuning or inference optimization in production.

Responsibilities

Design and ship production multi-agent systems, including orchestration, tool use, planning loops, memory, and failure recovery.
Build agents that use ServiceNow enterprise data, including CMDB, Workflow Data Fabric, and Knowledge Graph, to make context-aware decisions.
Own safety and governance controls for autonomous systems, including observability, human-in-the-loop controls, and compliance infrastructure.
Work with the search team to provide accurate, low-latency retrieval for agents, including RAG pipelines, hybrid search, re-ranking, and evaluation.
Integrate frontier models into the Sense → Decide → Act → Govern architecture and evaluate production trade-offs across cost, latency, and capability.
Provide technical leadership through architecture decisions, code reviews, and coaching, particularly on agentic design patterns and production AI practices.