Staff Machine Learning Engineer

About the role

AI Engineering and Delivery is the customer-obsessed engineering group building the agentic AI and enterprise-scale search systems that power Now Assist, AI Agents, and the AI-driven experiences our customers rely on every day. We build AI as foundational platform infrastructure - prioritizing robustness, performance, safety, and real-world customer impact at scale.

Your core focus areas

• 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.

To be successful in this role you have

• To be successful in this role you have:
• 5+ 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.
• Production-grade Python. Systems language (Go, Java, or C++) is a plus.
• 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.
• 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.

You'd work across three problem spaces at the frontier of what we do

• Autonomous Enterprise: Self-driving business processes grounded in CMDB, Workflow Data Fabric, and Knowledge Graph - context no frontier lab can replicate,
• Omni-channel AI Resolution: Production voice, chat, and computer-use agents with generative UI, live with customers today,
• Super Intelligence Control Tower: Identity, entitlements, and audit-grade compliance for every agentic system in the enterprise - nobody else has this layer.
• You will build the substrate that connects all four: SENSE (any data) -> DECIDE (any AI model) -> ACT (any workflow) -> GOVERN (identity + governance). The architectural inflection point is now.
• For positions in this location, we offer a base pay of $176,100 - $308,200, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure.

Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs.

Compensation is based on the geographic location in which the role is located and is subject to change based on work location.

Additional Information: Work Personas

We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.