Principal ML Engineer - Agentic AI Platform Architect

ServiceNow; California (MO); Hybrid; USD 240,000 - 420,000; Full time

Benefits offered by this job

Health plans

401(k) match

ESPP

Matching donations

Flexible time away

Family leave

Job summary

ServiceNow is expanding its AI Engineering and Delivery team to design and deploy agentic AI systems at enterprise scale. You will own multi-agent orchestration, tool calling, memory, and failure recovery, grounding agents in ServiceNow data layers and building robust production-grade workflows.

You will lead architectural decisions, collaborate across teams, and ensure safety, governance, and scalable deployment across hyperscalers. Base pay ranges with equity and benefits are offered.

Qualifications

• 9+ years of software engineering with 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.
• Production-grade Python; Systems language (Go, Java, or C++) is a plus.
• 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 — vector stores, hybrid search, and retrieval evaluation metrics.
• Track record of technical leadership: architecture ownership, code quality, and mentoring engineers on production AI practices.
• Nice to Have: 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, build, and help deploy production-grade agentic AI systems across ServiceNow's platform.
• Own multi-agent orchestration, tool calling, memory, and failure recovery in production.
• Ground agents in ServiceNow's data layers (CMDB, Workflow Data Fabric, Knowledge Graph).
• Establish guardrails: observability, human-in-the-loop controls, governance infrastructure.
• Integrate frontier models and evaluate cost, latency, and capability for production use cases.
• Set architectural patterns; lead design reviews and raise the bar on production AI practices.
• Design scalable, robust architectures for deployment across hyperscalers and our infrastructure.

Skills

Software engineering

Distributed systems

Python

Go

Java

C++

frontier AI SDKs

RAG

Leadership

Mentoring engineers

Tools

Python

Go

Java

C++

Job description

ServiceNow is expanding its AI Engineering and Delivery team to design and deploy agentic AI systems at enterprise scale. You will own multi-agent orchestration, tool calling, memory, and failure recovery, grounding agents in ServiceNow data layers and building robust production-grade workflows.

You will lead architectural decisions, collaborate across teams, and ensure safety, governance, and scalable deployment across hyperscalers. Base pay ranges with equity and benefits are offered.