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.
- Storytelling of impact — packages outcomes, generated value, and ROI into a clear narrative for the broader organization and senior leadership, building momentum and sponsorship.
- Executive presence and strong communication — translates between technical and business audiences and drives adoption of AI-enabled ways of working.
6. Governance, Risk & Regulatory Awareness
- Understands enterprise AI governance — model qualification, documented scope/limits, layered guardrails (private deployment, human-approval gates, audit trails), and risk-based tiering.
- Familiar with industry review/approval (legal, medical, regulatory, compliance); partners with Legal, Compliance, and Risk / Quality as co-owners, not end-stage approvers.
Preferred / Nice-to-Have
- Prior experience as the founding or lead product manager for an agentic AI or automation platform (versus a single AI feature).
- An earlier hands-on career in engineering (web, cloud, or ML) before moving into product.
- Experience in a highly regulated industry (e.g., pharma, healthcare, financial services, insurance).
- Direct exposure to AI evaluation frameworks and tooling (e.g., RAGAS, LLM-as-judge approaches, human-in-the-loop scoring platforms).
- Familiarity with MCP, LLM gateways, and multi-agent orchestration frameworks.
- Experience building or launching an internal ‘agent marketplace’ or centralized use-case intake / catalog process.
- Certification in Scrum / SAFe (CSPO, SAFe POPM) and/or AI product management coursework.
Qualifications
- Bachelor’s degree in a relevant field (Computer Science, Engineering, Information Systems) or equivalent experience; advanced degree a plus.
- 14+ years in product management / product ownership for technology platforms or products, including a proven track record of building AI and/or engineering products from scratch (0→1) and scaling them.
- 3–5 years working directly with AI/ML, automation, or agentic systems.
- Demonstrated end-to-end ownership — from product vision and use-case intake through delivery, adoption, and measurable business outcomes.
A portfolio or clear examples of products taken from concept to scale.
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.
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