Technical Product Owner, Discovery, Automation and Robotics (DAR)

3316 Takeda Development Center Americas•Boston, MA

14d•Onsite

About The Position

This role is 100% dedicated to Takeda R&D's Labs of Tomorrow Program. As the Technical Product Owner, you will be the technical delivery counterpart to the Business Lead for Takeda's next-generation AI-driven, automated laboratories. This role reports to the Head of Research, PharmSci and Labs DD&T. You will be day-to-day technical leader for Takeda's Discovery Automation and Robotics (DAR) 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 AI-native small molecule discovery capabilities, 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 combine strong 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.

Requirements

Bachelor's or Master's degree in Robotics, Automation, Systems Engineering, Computer Science, Bioinformatics, 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.
Knowledge of high throughput scientific workflows and prior hands-on automated laboratory experience (academic or industry) sufficient to understand scientific workflows, 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, computational scientists, data scientists, and ML scientists on design and trade-off discussions.
Working knowledge of modern software architecture, cloud platforms, data platforms, and AI/ML system design principles as applied to scientific software.
Experience translating ambiguous scientific or business requirements into clear, buildable technical specifications.
Strong stakeholder management skills, with the ability to partner effectively with a Business Lead as a joint leadership pair and to manage technical stakeholders across engineering, data science, and infrastructure teams.
Experience directing external technology/development partners, holding them accountable to technical scope, timeline, and quality.
Strong communication skills, able to translate between scientific stakeholders, business leadership, and technical delivery teams.
Ability to operate effectively in a complex, matrixed environment, influencing without direct authority.

Nice To Haves

Experience with scientific software platforms such as ELN/LIMS, compound registration systems, high-throughput experimentation (HTE) platforms, automated synthesis systems, or assay data platforms.
Exposure to cheminformatics tools, molecular data standards (e.g., SMILES, SDF, InChI), scientific data models, or AI-ready scientific data practices.
Experience with AI/ML-enabled discovery applications, including predictive modeling, generative chemistry, or agentic AI workflows.
Prior experience working in a laboratory automation or digital lab environment.
Relevant certifications in Agile/Scrum product ownership (e.g., CSPO, SAFe POPM).

Responsibilities

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.
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.