Principal Product Owner, AI

Bring more to life.

Are you ready to accelerate your potential and make a real difference within life sciences, diagnostics and biotechnology?

At IDBS, one of Danaher’s 15+ operating companies, our work saves lives—and we’re all united by a shared commitment to innovate for tangible impact.

You’ll thrive in a culture of belonging where you and your unique viewpoint matter. And by harnessing Danaher’s system of continuous improvement, you help turn ideas into impact – innovating at the speed of life.

At IDBS, we are at the cutting edge of providing innovative software solutions and services that empower scientists and researchers to accelerate their discoveries by helping them design, execute and orchestrate processes, manage, contextualize and structure their data and gain valuable insights throughout the drug lifecycle, from R&D through manufacturing. We work with 80% of the top 20 global BioPharma companies. Our customers engage in groundbreaking work, from pioneering biological research to developing new therapies and medicines. Join us at IDBS to continuously grow and make a real impact, working alongside passionate colleagues who care deeply about our mission and each other.

The Principal Product Owner, AI is responsible for owning the product backlog and delivery of AI capabilities across the Polar platform, transforming AI from generic chatbots into reliable, audit-defensible scientific colleagues. You will drive high-impact outcomes by translating retrieval-augmented generation (RAG) and model capabilities into bounded, grounded scientific workflows that accelerate discovery while protecting data integrity, compliance, and multi-tenant unit economics.

This position reports to the Senior Director, Platform Product Management and is part of the Platform Product Team and will be an office based role (based in the UK), however a remote position will be considered for the right candidate..

In this role, you will have the opportunity to:

Define AI Capabilities & Scope: Translate complex scientific and informatics workflows into outcome-focused, INVEST-compliant user stories with probabilistic acceptance criteria (grounding thresholds, citation requirements, latency tolerances, and explicit refusal behavior for unsupported queries).

Champion Benchmark & Evaluation Culture: Partner with Product Enablement and domain scientists to curate gold-standard evaluation datasets; establish rigorous regression gates and measure retrieval and generation quality (Recall, groundedness, hallucination rate, citation coverage).

Oversee Backlog & Agile Delivery: Lead sprint planning, refinement, and Program Increment (PI) planning for the AI feature team, collaborating closely with ML engineering, data engineering, and UX.

Bridge Platform & AI Integration: Partner with upstream data and platform teams to ensure seamless ingestion, metadata promotion, and data contracts across ELN, spreadsheet, and inventory data.

Govern Compliance, Security & Unit Economics: Ensure permission-aware retrieval and tenant isolation by design (supporting 21 CFR Part 11 and GxP standards) while monitoring token economics, latency, and quota utilization per tenant.

Drive Customer Adoption & Validation: Collaborate with pilot customers in Early Access and Design Partner programs to validate guided scenarios, isolate data hygiene from algorithm defects, and turn feedback into actionable product improvements.

The essential requirements of the job include:

Education: Bachelor’s degree (or equivalent practical experience) in Computer Science, Bioinformatics, Data Science, Engineering, or a related scientific/technical field.

Product Ownership Experience: Multiple years of experience as a Product Owner or Technical Product Manager delivering software products in Agile / Scrum or SAFe environments.

AI & RAG Fluency: Demonstrated hands-on experience defining specifications for retrieval-augmented generation (RAG), vector search, semantic retrieval, or LLM-driven features in software applications.

Data Integrity & Governance: Practical experience delivering software subject to strict enterprise data governance, tenant isolation, or regulatory/compliance standards (such as GxP, 21 CFR Part 11, ISO 27001, or equivalent).

Technical Backlog Elaboration: Proven ability to author technical user stories, acceptance criteria, and non-functional requirements (latency, throughput, cost/token bounds) for engineering and data science teams.

Travel, Motor Vehicle Record & Physical/Environment Requirements:

Travel: Occasional business travel required (up to 10–15%), including team PI planning events, customer visits, or company meetings.

It would be a plus if you also possess previous experience in:

Life Sciences Informatics: Direct exposure to Electronic Lab Notebooks (ELN), LIMS, CMC, or laboratory data management platforms.

Modern Cloud Data & AI Stack: Familiarity with AWS Bedrock, OpenSearch, Databricks, or Model Context Protocol (MCP) tool integrations.

Quantitative AI Evaluation: Experience operationalizing automated evaluation harnesses and prompt-testing pipelines (e.g., Ragas, TruLens, or custom benchmark suites).

#LI-Onsite

Join our winning team today. Together, we’ll accelerate the real-life impact of tomorrow’s science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life.

For more information, visit www.danaher.com .