New 
Senior Program Manager (Life Sciences Discovery)
 Microsoft | |
 United States, Washington, Redmond | |
 Oct 17, 2025 | |
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OverviewMicrosoft Discovery is a new enterprise Artificial Intelligence (AI) platform built on Azure to accelerate scientific Research and Development (R&D) with agentic AI - enabling researchers to collaborate with specialized AI agents and a graph-based knowledge engine for faster, smarter discovery. We are seeking a Senior Program Manager (Life Sciences Discovery) who will serves as a Life Sciences & Pharma R&D specilist to join the Microsoft Discovery product team. In this role, you will leverage deep domain expertise in biology and drug discovery to drive successful use cases on the platform, integrate scientific models and tools, and expand our life sciences partner ecosystem. You will collaborate closely with product engineering, research teams, customers, and industry partners to transform how Biotech, Pharma and Contract Research Organizations (CROs), organizations innovate using Microsoft's agentic AI technology. This is a high-impact individual contributor role, well-suited for someone passionate about connecting cutting-edge AI with real-world life sciences R&D. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and to create a culture of inclusion where everyone can thrive at work and beyond.
ResponsibilitiesKey Responsibilities: Use Case Development: Engage directly with pharmaceutical and biotech researchers to identify high-impact AI R&D use cases for Microsoft Discovery. Guide these projects from ideation through prototyping and deployment, demonstrating how agentic AI workflows (orchestrated AI agents with tools/models) can accelerate hypotheses generation, experimentation, and analysis. Customer Onboarding & Training: Lead the onboarding of new life sciences customers onto the Discovery platform. Ensure researchers can effectively use Discovery's capabilities (e.g. specialized agents, Azure High-Performance Computing (HPC) simulations) to solve their scientific challenges. Converting early wins into scalable playbooks and field adoption pattern. Agent & Model Integration: Collaborate with Microsoft Discovery engineers and data scientists to integrate domain-specific models, tools, and data sources into the platform. For example, help incorporate cheminformatics libraries, bioinformatics pipelines, lab automation tools, or proprietary models into Discovery's catalog. Define specialized AI agents and workflows that capture life sciences experimental processes and reasoning, enhancing the platform's ability to handle complex biological data and simulations. Partner Ecosystem Expansion: Identify and onboard strategic life sciences R&D partners - such as research institutions, biotech startups, ISVs, or data providers - whose tools or expertise can extend the Discovery platform's capabilities. Work with these partners to bring their data, models or IP onto Azure and integrate with our graph-based knowledge engine, creating a rich ecosystem of domain solutions on Discovery. Domain Leadership & Advocacy: Serve as the internal advisor for biology and pharma R&D. Champion the needs of scientists - ensuring features like experiment traceability, data provenance, and collaborative analysis are prioritized for trustworthy AI-assisted research. Provide proactive insights on industry trends (e.g. lab automation, computational biology, AI in clinical trials) and regulatory considerations to inform product strategy. Cross-Team Collaboration: Work cross-functionally to drive scenario success. Partner with architects to shape the product roadmap with life sciences requirements. Team up with Microsoft Research, Azure HPC, and Health & Life Sciences engineering groups to co-develop new capabilities (e.g. novel agent algorithms, specialized foundation models) that address gaps in the drug discovery process. Coordinate with field teams to align on customer engagements and ensure feedback loops from preview deployments drive continuous improvement. Impact Tracking: Define success metrics for life-sciences scenarios (e.g. reduction in experiment cycle time, number of novel insights generated by AI) and track the impact of Discovery deployments at customer sites. Thought leadership: Represent Microsoft's vision in the space across industry by contributing talks and presentation in industry and academic events. Other:Embody our Culture and Values | |