Staff AI Engineer, ServiceNow
Conversational & Agentic AI
$176.1-308.2k
Variable/incentive compensation
2+ days a week in office (Santa Clara, CA)
Cloud-based digital workflows for enterprises
Be an early applicant
Cloud-based digital workflows for enterprises
1001+ employees
Be an early applicant
$176.1-308.2k
Variable/incentive compensation
2+ days a week in office (Santa Clara, CA)
1001+ employees
Company mission
To transform IT to revolutionize the enterprise.
Role
Who you are
- 7+ 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
- Experience with multi-agent coordination patterns (A2A, MCP)
- Familiarity with agent frameworks (LangChain, LlamaIndex, or similar)
- Prior experience shipping AI systems in enterprise software
- Experience with AI observability tooling (tracing, cost tracking, LLM-specific monitoring)
- Familiarity with cloud-native infrastructure, service observability, logging, monitoring, reliability engineering, and production troubleshooting
What the job involves
- 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
- As a Staff AI Engineer, you will own significant parts of the agent harness — the infrastructure layer that enables AI agents to reason over real enterprise data, take action across workflows, and run safely at Fortune 500 scale
- Harness engineering: Design and build the agent execution harness — the orchestration layer that routes inputs, manages context, invokes tools, handles retries, and surfaces execution state across multi-step agentic workflows
- Reliability at scale: Own the runtime's fault tolerance, latency, and throughput; design for enterprise workflows that cannot fail silently or unpredictably
- Observability: Instrument the harness with tracing, cost attribution, and latency visibility so the team can reason about agent behavior in production and catch failures before customers do
- Prompt infrastructure: Build prompt management systems — versioning, templating, and systematic evaluation — that keep agent behavior stable across model updates and configuration changes
- Eval engineering: Design and own evaluation frameworks (unit evals, integration evals, production monitors) that measure agent quality, catch regressions, and drive data-informed decisions
- LLM integration: Integrate with and abstract over frontier LLMs, managing model routing, fallback strategies, cost, and latency trade - offs in production
- Technical leadership: Set technical standards through architecture decisions, code reviews, and coaching — particularly on agentic design patterns and production AI discipline
- System boundary design: Define where agent logic lives — what's a tool call, a sub-agent, a hardcoded path, or a human escalation — and establish those design standards across the team
Our take
ServiceNow provides cloud-based solutions that define, structure, manage, and automate services for enterprise operations, transforming old, manual ways of working into modern digital workflows. The company was founded in 2004 with a vision to build a cloud-based platform that would enable regular people to route work effectively through the enterprise.
Much as Salesforce enables a company to manage its external clients by keeping a record of all contacts and interactions, ServiceNow promises an internal system to meet the needs of employees. It has succeeded in claiming half the market, setting itself apart from legacy IT service-management software players like BMC Software, Hewlett Packard Enterprise, Cherwell Software and CA Technologies.
The company's success comes from two product traits: simplicity and customisability. ServiceNow's IT tools don't require the IT department to set them up. Once running, they offer a single collection centre for requests, data points and checklists, all of which can in turn be analysed by algorithms to predict needs, flag concerns and measure efficiency.
The company has more than 7,700 customers, including 85% of the Fortune 500 list of the United States' largest corporations. ServiceNow now looks to increase its revenue threefold in the upcoming years and has entered into a 5-year partnership plan with Visa, beginning with the launch of a Visa-integrated dispute resolution solution for issuers. The company is prioritising organic growth over mergers and acquisitions, with a target revenue of $15B, something which its Visa partnership will no doubt aid in achieving.
Freddie
Company Specialist at Welcome to the Jungle
Insights
16% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Mar 2012
$11m
GROWTH EQUITY VC
Feb 2012
$17.9m
GROWTH EQUITY VC
Total funding: $83.8m
Company benefits
- Generous family leave
- Matched donations
- Annual learning stipends
- Flexible PTO
- Competitive retirement plan
- Paid volunteer time
Company HQ
Santa Clara, CA
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