SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 190,900 - 334,100 / annual
ServiceNow's AI Engineering and Delivery team is building agentic AI and enterprise-scale search systems that power Now Assist, AI Agents, and AI-driven experiences across the platform. This role focuses on designing, building, and operating 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.
Core focus areas include:
**Agentic Architecture**: Design and ship multi-agent systems covering orchestration, tool use, planning loops, memory, and failure recovery that operate reliably in production environments, not just notebooks.
**Enterprise-Grounded Reasoning**: Build agents that leverage ServiceNow's data layer—CMDB, Workflow Data Fabric, and Knowledge Graph—to make decisions with context that frontier models lack on their own.
**Trust, Safety, and Governance**: Own the guardrails including observability, human-in-the-loop controls, and compliance infrastructure that make autonomous systems safe to deploy at scale.
**Retrieval and Grounding**: Work closely with the search team to ensure agents are grounded in accurate, low-latency retrieval through RAG pipelines, hybrid search, re-ranking, and evaluation.
**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.
ServiceNow operates 100B+ workflows, 6.5T transactions annually, and serves 85% of the Fortune 500. Current production systems include AI Specialists autonomously resolving cases across IT, CRM, HR, and Security; Action Fabric opening the system to external agents via MCP; Project Arc with NVIDIA for governed autonomous desktop agents; Build Agent live in Cursor, Claude Code, and GitHub Copilot; and AI Control Tower with kill-switch capabilities and cross-vendor agent governance.
You will work across three problem spaces: Autonomous Enterprise (self-driving business processes grounded in enterprise data), Omni-channel AI Resolution (production voice, chat, and computer-use agents with generative UI), and AI Control Tower (identity, entitlements, and audit-grade compliance for agentic systems).
**Requirements**:
- 8+ 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
