Lead Product Manager, AI Platform Products

We are seeking a hands-on Lead Product Manager to define, build, and ship AI-enabled platform products built on top of healthcare-grade data services and APIs. This role is ideal for a product leader who can turn complex underlying services into clear product requirements, workflows, and usable capabilities. You will work directly on a growing library of Model Context Protocol (MCP) tools built on top of established medication and clinical web services, with a focus on making those capabilities safe, reliable, and useful in AI-driven workflows. You will partner day to day with engineering, AI, clinical, and product stakeholders to define requirements, write user stories and acceptance criteria, prioritize roadmap decisions, and help bring new capabilities from concept through release. This role is best suited for someone who has built API-first or technically complex products, is comfortable working closely with engineering on detailed product decisions, and can move fluidly between customer problems, system behavior, and delivery execution. Healthcare experience is strongly preferred. Experience with MCP, tool orchestration, or agentic systems is a plus. What you\'ll do Define product strategy and roadmap for AI-enabled platform capabilities built on healthcare APIs and data services. Translate complex web services into clear product workflows, requirements, and implementation-ready product decisions. Partner closely with engineering to define product behavior for tool inputs, outputs, schemas, error handling, and platform usability. Write clear PRDs, user stories, acceptance criteria, and workflow definitions for new product capabilities. Work directly with engineering to break down ambiguous product problems into shippable increments. Help shape how products behave in AI-driven environments, including tool selection, tool sequencing, workflow logic, and multi-step orchestration patterns. Develop a strong understanding of the underlying data, service behaviors, and workflow logic that power the product. Help define product requirements for validation across technical correctness, functional tool invocation, robustness, clinical appropriateness, and end-to-end workflow performance. Partner with clinical and editorial stakeholders to ensure product behavior is safe, credible, and aligned to permitted use cases. Drive prioritization decisions across product features, testing capabilities, workflow support, and developer experience improvements. Create product artifacts such as PRDs, tool requirements, user stories, release requirements, use case definitions, and prioritization documents. Support internal and external product readiness by documenting intended product behavior, constraints, and rollout considerations. Balance near-term delivery with longer-term platform thinking, avoiding overbuilt solutions while building a foundation that can scale. Required qualifications 5+ years of product management experience, with meaningful ownership of technical, platform, or API-driven products. Experience building or managing API-first products, workflow products, developer platforms, or other technically complex systems. Demonstrated ability to work closely with engineering on technical requirements, integrations, schemas, delivery tradeoffs, and release execution. Proven experience writing product requirements, user stories, and acceptance criteria for engineering teams. Ability to understand structured data, service behavior, and API-driven workflows well enough to make effective product decisions. Experience with AI-enabled products, including products that rely on LLMs, decisioning systems, or structured tool invocation. Strong product judgment in ambiguous environments and the ability to turn loosely defined problems into clear next steps. Ability to translate complex technical systems into clear product requirements and business value. Strong written and verbal communication skills, with the ability to work effectively across product, engineering, AI, clinical, and business stakeholders. Experience defining product success metrics and operating with a test-and-learn mindset. Preferred qualifications Experience in healthcare, life sciences, clinical workflow, pharmacy, medication data, or regulated data products. Familiarity with clinical decision support, drug content, medication workflow products, or healthcare interoperability. Experience working with agentic systems, orchestration layers, or Model Context Protocol (MCP). Experience designing products that must balance usability, safety, auditability, and trust. Background working with evaluation frameworks for AI systems, including tool-call accuracy, workflow completion, and robustness testing. Experience partnering with domain experts in regulated or high-trust environments. What success looks like A clear and credible product plan for AI-enabled platform capabilities. Well-defined MCP tools and workflows grounded in real use cases and clear product requirements. Clear, actionable product requirements that help engineering move quickly and reduce ambiguity. Strong cross-functional alignment between product, engineering, AI, and clinical stakeholders. Faster, more consistent delivery of AI-enabled product capabilities built on top of core APIs. Validation approaches that reduce risk and improve confidence in product behavior before launch. Product decisions that improve adoption while respecting workflow realities, safety constraints, and implementation practicality. Why this role matters This role sits at the intersection of healthcare data, APIs, and AI-enabled workflow products. The work involves building a library of MCP tools on top of existing medication and clinical web services, where success depends not only on technical correctness, but also on reliable tool behavior, safe use in AI-driven experiences, and fit within real-world workflows. The product environment is highly cross-functional and requires close partnership across engineering, AI, and domain stakeholders. The role includes helping translate product goals into requirements that can be validated through tool behavior, workflow testing, and evidence-based iteration. Because the underlying services support concrete healthcare use cases such as drug interactions, allergy screening, duplicate therapy screening, contraindications, drug identification, and patient education, healthcare domain familiarity is valuable, but the most important quality is the ability to work hands-on with technical teams to turn complex systems into useful products. #J-18808-Ljbffr Wolters Kluwer