Lead Technical Product Owner, AI-native End Point Generation

By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice and Terms of Use . I further attest that all information I submit in my employment application is true to the best of my knowledge. Job Description Title: Technical Product Owner, AI-Native End Point Generation Location: Cambridge, MA About the role: As the Technical Product Owner, you will be the day-to-day technical leader for Takeda's AI-Native Endpoint Generation product family, working in direct partnership with the Business Lead to convert scientific and business intent into an executable technical roadmap. You will own the backlog, architecture direction, and delivery cadence for the development squads building an AI-native, integrated family of capabilities spanning the request, execution, and return of experimental data generated in external laboratories and through in vivo research, ensuring what gets built is technically robust, scalable, well-integrated with the broader Labs of Tomorrow ecosystem, and delivered in a way that enables the scientific and business value the Business Lead is accountable for. You will have technical product ownership discipline (backlog management, sprint planning, release management, stakeholder translation) with genuine high throughput laboratory automation fluency; enough to shape the redesign of laboratory workflows into AI-first workflows alongside the business, converse credibly with DAR scientists across the DMTA lifecycle, and make sound technical trade-offs that respect the underlying scientific method rather than working from a purely IT lens. You will operate at the product-team leadership level, working side-by-side with the Business Lead as a single aligned leadership pair, providing day-to-day direction to engineers, data scientists, ML scientists, and technical leads, and interfacing with other Technical Product Owners across the Labs of Tomorrow portfolio to ensure architectural coherence and reuse across the suite of products. This role is 100% dedicated to Takeda R&D's AI/ML Enablement Program. How will you contribute: Own and maintain the technical backlog and delivery roadmap for the DAR product family, translating the Business Lead's strategic vision and prioritized capabilities into epics, user stories, and technically sequenced releases. Partner with the Business Lead as a single accountable pair, jointly owning outcomes: the Business Lead is accountable for scientific/business value and adoption; the Technical Product Owner is accountable for technical feasibility, delivery quality, timeline, and platform integrity. Work with a team of Product Owners to translate re-imagined AI-native discovery workflows into clear technical requirements, acceptance criteria, and system designs in partnership with architects, engineers, data scientists, and ML scientists. Support use case level Scrum Masters for sprint planning, backlog grooming, story writing, and release management for the development squad(s), ensuring the team has clear, well-specified, de-risked work at all times, and that individual use cases within the product family are aligned. Make and own technical trade-off decisions (build vs. buy, sequencing, technical debt vs. new capability, integration approach) within the intent and priorities set by the Business Lead and Labs of Tomorrow leadership. Ensure technical solutions are grounded in real laboratory and computational workflows — validating that what is built reflects how chemists, structural biologists, and computational scientists actually work, not just how requirements were documented. Own integration and architectural alignment with adjacent platforms (ELN/LIMS, compound registration, HTE, automated synthesis, assay data platforms, scientific data lakes/data models) in coordination with enterprise architecture and other product teams. Manage technical risk, dependencies, and blockers across engineering, data, ML, and infrastructure workstreams, escalating and resolving with DD&T, Computational Science, and external delivery partners as needed. Define and track engineering KPIs (velocity, quality, technical adoption/usage telemetry, system performance, reliability) that complement the Business Lead's scientific and business value metrics, feeding a shared, integrated view of product health. Collaborate with our external technology/build partners on technical scope, architecture decisions, delivery timelines, and code/solution quality. Identify opportunities where AI agents, predictive models, automation, and data platform capabilities can be technically implemented to redesign scientific workflows, and translate these into feasible, well-architected product features. Partner with other Technical Product Owners across the Labs of Tomorrow portfolio to ensure extensibility, shared components, and consistent technical standards across the product suite. What you bring to Takeda: Bachelor's or Master's degree in pharmacology, biology, drug metabolism and pharmacokinetics, biomedical or veterinary science, computer science, or a related technical/scientific field; 8+ years of progressively responsible experience in software product ownership, technical program management, or engineering leadership, ideally within pharmaceutical, biotech, or life sciences R&D. Strong knowledge of discovery-stage experimental data generation, ideally including one or more of in vitro and in vivo pharmacology, drug metabolism and pharmacokinetics, translational and safety assessment, assay operations, externalized research delivery, and/or the management of contract research organizations, sufficient to understand scientificworkflows, laboratory processes, and the scientific reasoning behind discovery decisions, and to engage credibly with bench and computational scientists. Demonstrated experience as a Technical Product Owner, Product Manager, or similar role, owning a backlog and technical roadmap for a software product or platform end to end. Strong grounding in Agile/Scrum delivery: backlog management, story writing and acceptance criteria, sprint planning, release management, and cross-functional ceremonies. Hands-on technical background (prior coding, data engineering, or scientific computing experience) sufficient to engage credibly with software engineers, comput