Product Manager, Unified Experience Agentic Platform

Job description

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us. We are looking for a Product Manager, Agentic AI Platforms to set the product vision and own the roadmap for our enterprise AI & Engineering capability — a portfolio of AI agents and the shared engineering platform (orchestration, integration, AI operations, and quality) that powers them. This is a senior, vision-setting product role: you will decide what we build and why, take new agent concepts from concept to production, and grow the capability from point solutions into a governed, reusable platform that scales across the business. Understanding of AI and agentic systems is the anchor of this role — it is the primary skill we are hiring for. Around that anchor, you bring genuine engineering breadth (modern web development, cloud, and ML), the craft of product management, and the stakeholder leadership to align business, engineering, architecture, and governance. Above all, you bring a proven product vision and a track record of building AI and engineering products from scratch — not just running an existing backlog. You will report to the Leader — AI & Engineering and operate as a peer to architecture, engineering, AI operations, and delivery. Key Responsibilities - Set and evangelize the product vision and multi-quarter roadmap for the capability — the agent portfolio plus the platform that powers it. - Decide what to build and why: shape the agent portfolio, sequence delivery, and make build / buy / defer calls grounded in business value, feasibility, and risk. - Drive 0→1 product development — take new agent concepts from idea to prototype, MVP, and production, defining the minimum lovable product and iterating with real users. - Partner as a technical peer with architecture and engineering across web, cloud, and ML/LLM stacks — engaging on system design and trade-offs, not just handing over requirements. - Own a centralized use-case intake and evaluation process — assessing new agent proposals for business value, technical feasibility, and risk before they enter the roadmap. - Define and track success metrics for each agent and for the capability overall (adoption, quality/accuracy, cycle-time and effort savings, cost-to-serve) and report capability health to leadership. - Represent the end user and the business in every prioritization decision — pushing back when a technically impressive capability does not make the user’s experience genuinely better. - Champion governance — guardrails, human-in-the-loop checkpoints, audit trails, and risk-tiering — so agent capabilities scale without compromising compliance or safety. - Lead adoption and enablement — training, documentation, self-service, and change management as new capabilities roll out across teams and affiliates. - Partner with delivery and scrum leadership on PI planning, backlog refinement, and release sequencing; coordinate external delivery partners against scoped workstreams. - Represent the capability in steering committees and review boards, and make the business case that secures funding and sponsorship. Required Skills & Experience 1. AI & Agentic Systems Fluency (Anchor) - Anchor — deep, current grasp of LLMs and agentic systems — reasoning, planning, tools and data (RAG, tool-calling, MCP), context, and multi-agent orchestration. The primary skill for the role. - Shapes agent design with engineering as a peer (deterministic vs. judgement, tool/permission scoping, human-in-the-loop) and tells genuinely agentic products from scripted automation. - Sets quality bars and acceptance criteria — evals, LLM-as-judge, human scoring, version regression — and right-sizes models against cost, latency, and quality. 2. Product Vision & Building From Scratch (0→1) - Critical — proven track record of building AI/engineering products from scratch (0→1): concept → MVP → production → scale, with real adoption and measurable outcomes — not just running a backlog. - Clear, opinionated product vision — turns ambiguous, greenfield problems into strategy, a sequenced roadmap, and shippable increments; thrives amid fast-moving tech. - Has scaled POC/point solutions into governed, reusable platforms — tying bets to business value, funding, and measurable ROI. 3. Engineering & Technical Breadth - Genuine fluency across modern web development, cloud (identity, CI/CD), and ML/AI (model lifecycle, data pipelines, MLOps). - Holds their own in architecture discussions — system design, dependencies, integration, scalability, trade-offs — without needing to write production code; understands platform engineering and DevEx as scale levers. - Familiar with the systems agents integrate with (CMS, CRM, ticketing, ERP) and standard tooling (Jira, Azure DevOps, Confluence, Figma); prior hands-on engineering a plus. 4. Product Management Craft - Strong PM fundamentals — discovery, roadmapping, prioritization (RICE, WSJF), acceptance criteria, and release sequencing across a multi-consumer platform. - Metrics-driven with strong UX instincts — tracks adoption, quality, and cost-to-serve; prioritizes ruthlessly and says no while keeping stakeholder trust. 5. Stakeholder & Executive Leadership - Leads cross-functional teams (architecture, engineering, data science / ML, design, business) and manages external delivery partners against scoped workstreams. - Story