Director, Product Management- AI Agent Products

ServiceNow is a company focused on AI-driven business solutions, and they are seeking a Director of Product Management to lead the product vision and execution for AI agent products. This role involves defining the product's long-term vision, architecting capabilities, and driving adoption of autonomous agents within enterprises.

Responsibilities:

• Actively prototype, experiment, and ship using modern agentic development tools as a core part of your job
• Engage directly with code: review implementations, stand up demos, and validate feasibility alongside engineering
• Use hands-on experimentation to de-risk product bets and accelerate time-to-market
• Stay at the leading edge of agentic AI, autonomous agents, open-source frameworks, orchestration patterns, memory architectures, and translate that into concrete product capabilities
• Define and drive the product's long-term vision: autonomous agents enterprises trust to do real work, from desktop execution to orchestrated workflows across systems
• 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 that can be leveraged across this product and other ServiceNow AI offerings
• Partner with frontier AI teams and the open-source ecosystem to bring state-of-the-art capabilities into enterprise production
• Define clear adoption paths and usage models for agentic capabilities across customer segments
• Partner with go-to-market and outbound teams to ensure time-to-value and measurable impact
• Establish metrics early. Task completion rates, success rates, latency, cost per action, and iterate rapidly against them
• Engage with external ecosystem players and partners as needed to accelerate roadmap and adoption
• Balance near-term customer deliverables with long-term platform differentiation and governance innovation

Requirements:

• 8-10+ years of product management experience, recent hands-on experience shipping agentic products in the last 12–18 months. Years of PM tenure matter far less than what you've shipped recently and how deep you've gone technically
• Comfortable working in codebases, standing up prototypes, and challenging engineering decisions with technical credibility
• Background as a developer is a strong plus; exceptional PMs with adjacent technical depth are a match
• Strong understanding of modern AI systems and agent architectures: planning, memory, tool use, orchestration, multi-step reasoning
• Deep familiarity with the frontier of agentic AI: open-source frameworks, agent loop patterns, LLM orchestration, and the fast-moving research being published today
• Ability to translate fast-moving research into practical, productizable capabilities without waiting for consensus
• You follow the agentic AI community, contribute to or build on open-source projects, and stay connected to emerging patterns
• Proven product management experience (minimum 8 years), with hands-on involvement in shipping complex products in ambiguous, fast-moving environments
• Track record of shipping 0→1 and scaling 1→N products. You've brought something to market that didn't exist before and then scaled it
• Ability to operate across multiple teams: engineering, design, GTM, partners and create alignment without authority
• Thrives in ambiguity, creates structure where none exists, and pulls products forward through clarity and credibility, not process
• You think in platforms, not features. You see how pieces connect and can architect primitives that multiply value across multiple products and use cases
• You influence by showing, not telling. You paint a compelling picture of what's possible, one that VPs and executive teams want to be part of
• Experience working on or shipping multi-agent systems, agentic orchestration platforms, or agent deployment frameworks
• Hands-on involvement with LLM fine-tuning, prompt engineering at scale, or domain-specific model development
• Track record of working with open-source communities, contributing to or building on open frameworks
• Prior experience in enterprise workflow automation, RPA, or low-code/no-code platforms. Understanding the operational constraints enterprises face
• Familiarity with governance, compliance, and auditability requirements for enterprise AI systems
• Experience working with frontier AI providers or integrating cutting-edge models into production systems