Role Overview
Our client, a Bay Area-based security technology company, is seeking a seasoned AI Project Manager to lead and coordinate its enterprise AI initiatives across multiple tracks. This is a pure project management role — not a developer, data scientist, or business analyst position. The ideal candidate has personally managed the delivery of an AI/LLM-based initiative (not just AI-adjacent automation) and can speak fluently and specifically to that experience. Strong executive presence, stakeholder management, and communication skills are essential, as this role requires regular engagement with senior and cross-functional stakeholders.
Must-Have Qualifications (Non-Negotiable)
•MUST HAVE: Direct, hands-on experience managing a project built around a Large Language Model (LLM) — Anthropic Claude experience strongly preferred — within the last 1–2 years. Candidates must be able to describe the LLM(s) used, the use case, architecture at a PM level, and measurable outcomes.
•MUST HAVE: Demonstrated ownership of AI-specific project delivery (model integration, prompt/workflow design coordination, evaluation cycles, AI vendor/tooling management). General "automation" or "digital transformation" experience without AI/LLM specificity does not qualify.
•MUST HAVE: Minimum 10–12 years of overall Project Management experience, including a track record of managing automation-focused programs.
•MUST HAVE: Executive-level communication and articulation skills, with proven experience managing critical, senior, and sometimes difficult stakeholders across business and technical functions.
Core Responsibilities
•Own end-to-end delivery of the client''s AI initiatives across multiple concurrent tracks (workstreams, timelines, budgets, and dependencies).
•Serve as the primary point of coordination between business stakeholders, technical/AI teams, and vendors — translating technical AI concepts into business impact and vice versa.
•Define and track project plans, milestones, RAID logs, and status reporting tailored to AI/LLM project nuances (e.g., model evaluation cycles, prompt iteration, data readiness, compliance review).
•Facilitate governance, steering committee updates, and executive readouts on AI program progress and risk.
•Drive alignment across cross-functional teams (engineering, security, compliance, product) to keep AI tracks on schedule and within scope.
•Proactively identify risks specific to AI initiatives (model performance, data privacy, third-party authentication, change management) and drive mitigation.
•Manage vendor and third-party relationships tied to AI tooling and platforms.
Ideal Candidate Profile
•A seasoned PM (10-12+ years) who has personally sat in the driver''s seat of an AI/LLM initiative — not someone who supported one peripherally.
•Comfortable being asked pointed, specific questions about their AI project experience (which LLM, what was built, how success was measured, what stakeholders were involved).
•Confident, articulate communicator capable of managing up to senior/executive stakeholders and holding ground in critical conversations.
•Structured, process-driven, and comfortable operating with formal PM methodology (Agile/Waterfall/hybrid) in an enterprise setting.
•Prior experience in security, fintech, or other regulated/enterprise environments is a plus.
What Will NOT Be Considered
•Candidates whose only AI exposure is passive awareness, training, or certifications without hands-on project delivery.
•Developers, analysts, data scientists, or ML engineers looking to transition into PM roles without existing PM tenure.
•Generic automation/RPA project management experience with no LLM/AI component.
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