Director, AI Product Development - Medical

AstraZeneca•Gaithersburg, MD

1d•Hybrid

About The Position

The Director, AI Product Development, Medical is a product leadership role within AstraZeneca’s AI for Commercial team in the Enterprise AI organization. The role leads the design, development, launch, and adoption of generative AI and machine-learning products for Medical Affairs across Oncology, BioPharma, and Rare Disease, at global and market levels. These products support medical colleagues in generating insights, engaging scientifically with healthcare professionals, and translating evidence into decisions. The director owns the end-to-end product lifecycle, defines the roadmap and priorities across business units, leads cross-functional execution, and is accountable for measuring business impact. The role promotes reusable enterprise platforms and shared capabilities rather than isolated solutions, and operates within responsible AI, medical, privacy, and IT governance requirements. AstraZeneca expects employees to work from the office an average of at least three days per week, while allowing for individual flexibility.

Requirements

Advanced degree (MS, PhD, PharmD, or MD) in a quantitative or scientific discipline, such as Computer Science, Statistics, Engineering, Life Sciences, or Epidemiology, or equivalent.
At least 7 years of experience building and shipping data science or AI products in a commercial or life sciences setting.
At least 3 years in Pharmaceutical or Life Sciences with direct exposure to Medical Affairs.
Familiarity with medical data domains such as scientific insights, publications, medical information, real-world evidence, or HCP engagement.
Demonstrated experience owning an AI product end to end, including requirements, development, deployment, and post-launch measurement.
Working knowledge of modern AI approaches, including LLMs, retrieval-augmented generation, and agentic workflows, sufficient to scope use cases, evaluate technical tradeoffs, and write executable requirements for engineering teams.
Strong product skills, including defining user needs, writing clear requirements, prioritizing a backlog, and communicating tradeoffs to stakeholders.
Experience delivering solutions on shared enterprise platforms in partnership with IT and technology functions.

Nice To Haves

PhD, PharmD, or MD and a track record of translating scientific research into applied products.
Experience delivering AI products for Medical Affairs, such as insight analytics, content augmentation, scientific engagement, or predictive engagement.
Working knowledge of medical platforms and integration patterns, including Veeva, Salesforce, knowledge management, and DAM.
Understanding of global and local medical regulations, scientific exchange standards, and responsible AI governance practices.
Background spanning multiple functions, such as Medical Affairs, Commercial, Market Access, or Insights & Analytics.
Demonstrated ability to drive user adoption at scale through role-based training, change management, and usage analytics.
Experience managing external vendors and consultants against defined deliverables and timelines.
Strong executive communication skills and comfort presenting product roadmaps and business cases to senior leadership in a matrixed organization.

Responsibilities

Own the full AI product lifecycle, from problem definition and customer research through AI development, UX design, deployment, adoption, and measurement.
Lead development of generative AI and agentic AI products for Medical Affairs.
Define product requirements and functional specifications for AI applications, agentic workflows, and evaluation and quality frameworks serving headquarters and field medical teams.
Translate high-value medical use cases into product requirements in partnership with Medical leadership and teams including Field Medical Excellence, Medical Informatics, Scientific Communications & Content Strategy, Evidence Generation (RWE/HEOR), Scientific Engagement, and Patient Solutions.
Leverage shared enterprise platforms, data assets, and reusable components; challenge duplicative or one-off solution requests and redirect them toward common capabilities.
Partner with technical delivery leads, engineering, data science, and IT to deliver scalable, governed, high-quality solutions on time.
Establish clear RACI, align priorities, and drive accountability across the cross-functional delivery model.
Define success criteria before launch and measure usage, output quality, and downstream impact, including cycle-time reduction for insight synthesis, content development, and planning.
Communicate product results clearly to leadership.
Ensure products operate within responsible AI and medical governance, including scientific exchange standards, promotional and non-promotional boundaries, privacy and data access controls, vendor management, IT approvals, human-in-the-loop oversight, and documentation.
Set product roadmaps and priorities across business units, balance therapy-area demands, manage scope transparently, and sequence delivery around critical milestones and shared capabilities.
Monitor GenAI, agentic AI, and pharmaceutical AI trends; identify strategically relevant capabilities, pilot solutions, and champion modular reuse, scalability, and accelerated deployment across business units, functions, and markets.