Principal Product Manager, AI

Responsibilities

• Set and drive the Agentic AI vision: Define multi-year, company-level Agentic AI strategy spanning product lines.
• Translate vision into portfolios, roadmaps, and investment frameworks for AI agents, copilots, and automation.
• Scan AI landscape and integrate innovations durably and compliantly.
• Build and execute AI platform strategy to enable AI feature development.
• Lead end-to-end product discovery and delivery for AI agents, including problem framing, design, deployment, guardrails, and optimization.
• Define success metrics (task completion, latency, precision/recall, cost) and drive experimentation.
• Partner with Engineering and AI/ML on architecture, model selection, tools, retrieval, and safety.
• Design MCP-based ecosystems of tools, actions, and data connectors for agents.
• Define agent orchestration patterns (multi-agent, planner-executor, human-in-the-loop).
• Ensure agents handle enterprise requirements (identity, permissions, data locality).
• Embed AI into other product pillars' roadmaps for cohesive workflows.
• Run cross-functional rituals to align AI with company goals.
• Partner with GRC experts, Sales, CS to validate use cases.
• Spend time with customers to understand needs and prioritize AI opportunities.
• Champion AI product quality, UX, explainability, and transparency.
• Create operating models, frameworks for AI product development.
• Mentor senior PMs on strategy, storytelling, metrics.
• Represent AI vision internally and externally.

Requirements

• 10+ years product management experience, significant time as senior/lead PM owning complex areas.
• 3–5+ years building/shipping AI/ML or LLM products, 2+ years on agentic systems/copilots in production.
• Experience designing, deploying, iterating AI agents with evaluation, guardrails, observability.
• Deep understanding of agentic ecosystem and MCP (tools/plugins, actions, function calling, retrieval, orchestrators).
• Strong technical fluency: read API docs, reason about data/model tradeoffs, architecture decisions.
• Track record defining multi-year strategy in ambiguous domains, influencing execs.
• B2B SaaS experience; GRC/security/risk familiarity preferred.
• Exceptional communication to align stakeholders and explain AI concepts.
• Customer-obsession with history of high-impact bets from insights.

Nice-to-haves

• Experience in GRC, Security, or TPRM.