Job DescriptionAbout the TeamThe 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 12 Decide 12 Act 12 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.
QualificationsTo 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 InformationWork PersonasWe 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.
