Director, Product Management – AI Agent Products

Job Description

ServiceNow is hiring a Director of Product Management to lead product vision and execution for a transformational frontier AI agent currently at MVP stage. This is a builder's role: you'll define how enterprises deploy long-running, self-evolving autonomous agents for knowledge workers, connect them natively to ServiceNow's AI infrastructure, and bring governance and auditability to every agent action at enterprise scale.

This is a 0→1 product leadership seat on a team that operates like a startup inside a large enterprise. You'll prototype capabilities ahead of the roadmap, work hands-on in code alongside engineering, and translate frontier AI research into platform primitives that drive adoption across ServiceNow's broader AI portfolio.

Key Responsibilities

• Own the long-term product vision for autonomous agents that enterprises trust to do real work — from desktop execution to orchestrated cross-system workflows.
• Architect the roadmap for agentic platform capabilities: orchestration, memory and context management, action execution, endpoint interaction, and secure agent governance.
• Translate emerging agent patterns into scalable platform primitives reusable across other ServiceNow AI products.
• Partner with frontier AI teams and the open-source ecosystem to bring state-of-the-art agent capabilities into enterprise production.
• Actively prototype and ship using modern agentic development tools — reviewing implementations, standing up demos, and validating feasibility directly with engineering.
• Define clear adoption paths and usage models for agentic capabilities across customer segments, partnering with go-to-market teams on time-to-value.
• Establish and iterate against core metrics: task completion rate, success rate, latency, and cost per action.
• Balance near-term customer deliverables against long-term platform differentiation and governance innovation.

Requirements

• 8–10+ years of product management experience, with hands-on shipping of agentic products in the last 12–18 months — recency of technical depth matters more than raw tenure.
• Comfort working directly in codebases: standing up prototypes and challenging engineering decisions with technical credibility.
• Strong understanding of modern agent architectures — planning, memory, tool use, orchestration, and multi-step reasoning.
• Deep familiarity with the frontier of agentic AI: open-source frameworks, agent loop patterns, and LLM orchestration.
• Proven track record shipping 0→1 products and scaling them 1→N.
• Ability to align engineering, design, and go-to-market teams without formal authority, in ambiguous, fast-moving conditions.

Preferred

• Experience shipping multi-agent systems, agentic orchestration platforms, or agent deployment frameworks.
• Hands-on involvement with LLM fine-tuning or prompt engineering at scale.
• Track record contributing to or building on open-source AI frameworks.
• Background in enterprise workflow automation, RPA, or low-code/no-code platforms.
• Familiarity with governance, compliance, and auditability requirements for enterprise AI systems.
• Experience integrating frontier AI providers' models into production systems.