Staff Machine Learning Engineer

Posted 5 Hours Ago
Be an Early Applicant
Santa Clara, CA, USA
Hybrid
176K-308K Annually
Senior level
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
We're putting AI to work for people.
The Role
Design, build, and operate production-grade agentic AI systems for ServiceNow. Responsibilities include multi-agent orchestration, tool use, planning, memory, failure recovery, enterprise-grounded reasoning, RAG and search pipelines, safety guardrails, observability, model integration, evaluation frameworks, and cost and latency optimization. The role also provides technical leadership through architecture decisions, code reviews, and coaching.
Summary Generated by Built In
Company Description

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.

Join us to put AI to work for people.

 

Job Description

About the Team

The Agentic Engineering organization at ServiceNow is the customer-obsessed engineering group that builds a conversational AI experience that turns enterprise intent into completed work. We advance how enterprise AI reasons, remembers, and executes.

The Agent Orchestration team — the team you'll join — owns the execution core: the agent harness, orchestration runtime, multi-agent coordination, memory management, and the evaluation frameworks that ensure agents behave correctly in production. Every autonomous action Otto promises depends on what this team ships.

By joining our team, you’ll be at the forefront of our AI transformation journey, backed by the global scale of ServiceNow and the agility of a high-growth environment. We are looking for world-class talent to help us extend agentic AI to every employee across every corner of the business

You will design, build, and operate production-grade agentic AI systems embedded across ServiceNow's platform — autonomous agents that reason over real enterprise data, take action across workflows, and run safely at Fortune 500 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. 

Qualifications

To be successful in this role you have:

  • 6+ years building production software systems with a strong track record on reliability, performance, and scalability
  • Hands-on experience shipping generative AI products — not just integrating LLM APIs or building prototypes, but owning AI-powered features that production users depend on
  • Solid depth in how large language models work: failure modes, context constraints, and how prompt design shapes model behavior at scale
  • Practical prompt engineering experience: systematically designing, versioning, and evaluating prompts across model updates or A/B evaluation cycles
  • A real track record in eval engineering — not just familiarity, but a portfolio of evaluation suites designed, shipped, and used to drive quality decisions in production AI systems
  • Cost and efficiency awareness at the system level: experience reasoning about model routing, inference cost, and latency tradeoffs in production
  • Strong software engineering fundamentals: distributed systems, API design, and testing discipline
  • Comfort operating in fast-moving, ambiguous, startup-like AI product environments

Nice to Have

  • Exposure to AI services deployed in a micro services-based architecture (Kubernetes, OpenShift, etc.)
  • Experience tracing, debugging, identifying root causes, and resolving issues in AI codebases that span multiple services, multiple environments, and/or multiple tenants
  • Published work, patents, or open-source contributions in Machine Learning, AI, distributed systems, etc.

 

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.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity,  veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.  

Accommodations

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [email protected] for assistance. 

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. 

From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

Skills Required

  • 6+ years building production software systems with demonstrated reliability, performance, and scalability experience
  • Hands-on experience shipping generative AI products used by production customers
  • Strong understanding of large language models, including failure modes, context constraints, and prompt design
  • Practical experience designing, versioning, and evaluating prompts
  • Track record in evaluation engineering, including production evaluation suites used for quality decisions
  • Experience with model routing, inference cost, and latency tradeoffs
  • Strong software engineering fundamentals, including distributed systems, API design, and testing
  • Comfort working in fast-moving, ambiguous, startup-like AI product environments
  • Exposure to AI services deployed in microservices architectures such as Kubernetes or OpenShift
  • Experience tracing, debugging, root-cause analysis, and issue resolution across multiple AI services, environments, or tenants
  • Published work, patents, or open-source contributions in machine learning, AI, or distributed systems

What the Team is Saying

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ServiceNow Compensation & Benefits Highlights

  • Healthcare Strength Healthcare is described as comprehensive, with employer‑verified medical, dental, vision, life and disability coverage plus mental‑health support. Feedback suggests plan breadth and quality are a standout element of the package.
  • Leave & Time Off Breadth Time off options include flexible PTO, paid holidays, paid volunteer time, and additional company “Wellbeing Days.” Feedback suggests employees value the breadth of recharge time available.
  • Equity Value & Accessibility Ownership programs feature a 15%‑discount Employee Stock Purchase Plan alongside role‑based equity (e.g., RSUs) and performance bonuses. Feedback suggests these elements meaningfully lift total compensation beyond base pay.

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The Company
HQ: Santa Clara, CA
29,000 Employees
Year Founded: 2004

What We Do

As the AI platform for business transformation, we're putting AI to work across organizations — freeing people for work that matters. Making old tech work with new tech. Reaching across departments, from the front office to the back office and every office in between. Our ambition? To become the AI defining enterprise software company of the 21st century (or "AI DESCO21C," as we like to call it). With more than 8,400+ customers, we serve approximately 90% of the Fortune 500®, and we're proud to be a Fortune 100 Best Companies to Work For® and World's Most Admired Companies™. Explore your future career with us, visit www.careers.servicenow.com From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

Why Work With Us

By joining ServiceNow, you are part of an ambitious team of change-makers who have a restless curiosity and a drive for ingenuity. We're committed to helping our people do their best work and live their best lives so we can fulfill our purpose together. At the fastest-growing enterprise software company, you can grow your career faster.

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ServiceNow Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

At ServiceNow, we lead with flexibility and trust. For some, home is the primary workplace. For those who come into a ServiceNow workplace, you are empowered to make team-guided and individual-led decisions on how and when you use the workplace.

Typical time on-site: Flexible
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