Director, AI Product Development - Medical

AstraZeneca•Gaithersburg, MD

1d•$186,014 - $279,021•Hybrid

About The Position

This is a product leadership role at the center of how AstraZeneca’s Medical Affairs organizations work. You will own the end-to-end product development of AI-powered solutions that put AI, agentic workflows, and evaluation and quality framework into the hands of medical colleagues across headquarters and the field, changing how scientific evidence is generated, communicated, and acted on for patients and healthcare professionals. The Director, AI Product Development, Medical is part of the AI for Commercial (AIC) team within the Enterprise AI organization. You will lead the design, build, launch, and adoption of GenAI and ML-powered products that serve Medical Affairs organizations across Oncology (OBU), BioPharma (BBU), and Rare Disease (RDU), at Global and market levels. Your products will change how medical colleagues generate insights, engage scientifically with healthcare professionals, and translate evidence into decisions. You define the roadmap, drive cross-functional execution, and are accountable for measured business impact.

Requirements

Advanced degree (MS, PhD, PharmD, or MD) in a quantitative or scientific discipline (Computer Science, Statistics, Engineering, Life Sciences, Epidemiology, or equivalent)
7+ years of experience building and shipping data science or AI products in a commercial or life sciences setting
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: requirements, development, deployment, and post-launch measurement
Working knowledge of modern AI approaches (LLMs, retrieval-augmented generation, agentic workflows) sufficient to scope use cases, evaluate technical tradeoffs, and write requirements that engineering teams can execute against
Strong product thinking: ability to define user needs, write clear requirements, prioritize a backlog, and communicate tradeoffs to stakeholders
Experience delivering solutions on shared enterprise platforms in partnership with IT and technology functions

Nice To Haves

PhD, PharmD, or MD with a track record of translating scientific research into applied products
Experience delivering AI products for Medical Affairs (insight analytics, content augmentation, scientific engagement, or predictive engagement)
Working knowledge of medical platforms and integration patterns (Veeva, Salesforce, knowledge management, DAM)
Understanding of global and local medical regulations, scientific exchange standards, and responsible AI governance practices
Background spanning multiple functions: Medical Affairs, Commercial, Market Access, or Insights & Analytics
Demonstrated ability to drive user adoption at scale: role-based training, change management, and usage analytics
Experience managing external vendors and consultants against defined deliverables and timelines
Strong executive communication skills; comfortable 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. This means shipping products, not delivering reports.
Lead GenAI and agentic AI product development for Medical Affairs. Define product requirements and functional specifications for AI-powered applications, agentic workflows, and evaluation and quality framework that serve headquarters and field medical teams across therapeutic areas.
Translate high-value medical use cases into product requirements. Partner with Medical leadership, Field Medical Excellence, Medical Informatics, Scientific Communications & Content Strategy, Evidence Generation (RWE/HEOR), Scientific Engagement, and Patient Solutions to align product capabilities with therapy area strategy, scientific engagement priorities, and field workflows.
Build on enterprise AI foundations rather than BU-specific silos. Leverage shared platforms, data assets, and reusable components so that capabilities built for one BU extend to others. Actively challenge duplicative or one-off solution requests and redirect them toward common capability.
Partner with technical delivery leads, engineering, data science, and IT teams to translate requirements into scalable and governed solutions and ensure high-quality, on-time execution. Establish clear RACI, maintain alignment on priorities, and drive accountability across a cross-functional delivery model.
Drive adoption and value realization. Define success criteria before launch; track usage, output quality, and downstream impact post-launch, including cycle time reduction for insight synthesis, content development, and planning. Communicate results to leadership with clarity.
Operate within responsible AI and medical governance. Navigate scientific exchange standards, promotional and non-promotional boundaries, privacy and data access controls, vendor management, and IT approval processes. Ensure human-in-the-loop oversight and appropriate documentation for all deployed products.
Set the product roadmap and prioritization across BUs. Balance competing therapy area demands, manage scope with transparency, and sequence delivery to protect critical milestones while building toward shared capability rather than one-off solutions.
Stay current with GenAI, agentic AI, and pharma AI trends. Identify emerging capabilities with strategic fit, pilot solutions with speed and rigor, and champion a platform-centric approach that enables modular reuse, scalability, and accelerated deployment across BUs, functions, and markets.