Staff AI Platform Engineer — Enterprise Agentic AI

ServiceNow

California (MO)

Hybrid

USD 176,000 - 308,000

Full time

14 days+
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Benefits offered by this job

Health plans
401(k) Plan with company match
ESPP (employee stock purchase)
Matching donations
Flexible time away
Family leave programs

Job summary

ServiceNow is building an AI-native platform and leading a team that develops agentic AI systems at Fortune 500 scale. You will design, build, and operate production-grade autonomous agents that reason over enterprise data, take action across complex workflows, and run safely in production.

You will own AI-powered features, drive evaluation and AB testing, optimize for cost and latency, and shape engineering practices through architecture reviews and production discipline.

Qualifications

  • Production AI experience required.
  • Own AI-powered features in production.
  • Strong knowledge of large language models and failure modes.
  • Experience with eval engineering and AB testing.
  • Ability to optimize cost, latency, and throughput.
  • Solid fundamentals in distributed systems and API design.

Responsibilities

  • Design and ship multi-agent systems for production.
  • Ground enterprise data using CMDB, Knowledge Graph.
  • Own guardrails: observability, human-in-the-loop controls.
  • Integrate frontier models (Anthropic, Google, OpenAI).
  • Lead architecture decisions and code reviews.
  • Coach teams on production AI discipline.

Skills

Production software
Generative AI
LLMs knowledge
Prompt engineering
Evaluation engineering
Distributed systems
APIs and testing

Tools

Kubernetes
OpenShift
Microservices

Job description

ServiceNow is building an AI-native platform and leading a team that develops agentic AI systems at Fortune 500 scale. You will design, build, and operate production-grade autonomous agents that reason over enterprise data, take action across complex workflows, and run safely in production.

You will own AI-powered features, drive evaluation and AB testing, optimize for cost and latency, and shape engineering practices through architecture reviews and production discipline.

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