Associate Director, Clinical AI Translation & Solutions

Introduction To Role Are you ready to turn complex clinical workflows into safe, measurable AI systems that accelerate trials and meaningfully improve patient outcomes? This role sits at the heart of how we design, conduct, monitor, and analyze clinical studies—translating real-world operations into AI solutions that scale across the enterprise and deliver tangible business value. Job Title: Director, AI Research You will work side‑by‑side with clinical professionals and engineers to observe how work truly happens, identify where AI can safely help, and translate that understanding into working software. Do you thrive on building hands‑on prototypes, making disciplined scope decisions, and staying accountable through evaluation, deployment, adoption, and iteration? Your initial focus will include agentic workflows for clinical operations, with the expectation that reusable patterns will extend across Clinical Development. Accountabilities Portfolio Ownership: Own a portfolio of clinical AI workflows from discovery through deployment, adoption, and measurable benefit realization, ensuring early wins become platform capabilities. Workflow Discovery and Design: Observe CRAs, site-monitoring leaders, clinical operations, and medical stakeholders to convert pain points into product requirements, data contracts, acceptance criteria, and evaluation plans. Hands‑on Prototyping and Delivery: Build and iterate prototypes in Python; contribute production code, review pull requests, inspect logs, reproduce failures, and collaborate with engineers to resolve them. Agentic Workflow Design: Combine language models, deterministic services, enterprise tools, and human review with clear evidence provenance, uncertainty handling, and fail‑safe behavior. Scope and Release Discipline: Separate demonstrations from production releases and distinguish non‑GxP workflows from regulated use, making transparent risk and lifecycle trade‑offs. Outcome Measurement: Define outcome measures spanning technical performance, clinical usefulness, workflow quality, user adoption, cycle time, and operational impact. Human‑in‑the‑Loop Testing: Lead testing with clinical experts and translate feedback into prioritized, testable product changes that increase trust and adoption. Data Access and Governance: Partner with data‑product owners and platform teams to establish reliable access to clinical systems, documents, and structured data while protecting privacy and integrity. Compliance by Design: Collaborate with Quality, Regulatory, Privacy, Security, and R&D IT to embed GCP, GxP, validation, auditability, and lifecycle requirements from the outset. Reuse and Build/Buy Decisions: Promote reuse of enterprise platforms, data products, agent components, and evaluation assets; identify when to build, buy, partner, or adapt. Communication and Influence: Communicate product decisions, evidence, risks, dependencies, and trade‑offs clearly to technical teams, clinical leaders, and executives. Mentorship and Standards: Mentor scientists and engineers and raise the team’s standard for product thinking, technical execution, and clinical partnership. Essential Skills/Experience PhD in Computer Science, Machine Learning, Statistics, Biomedical Informatics, Computational Biology, or a related quantitative discipline; or an MD, master’s degree, or equivalent experience supported by a strong computational track record. 4 to 7 years of post-PhD (or equivalent) experience delivering applied AI/ML or data products, including experience in healthcare, life sciences, clinical research, or another high‑consequence domain. Current, hands‑on coding ability in Python and SQL, with experience using version control, tests, APIs, data pipelines, and modern cloud or containerized development environments. Experience building or deploying LLM-based or agentic systems, including retrieval, tool use, structured outputs, workflow orchestration, and human review. Demonstrated ability to translate ambiguous stakeholder needs into a bounded product, working prototype, measurable acceptance criteria, and delivery plan. Ability to lead workflow‑discovery and design sessions with clinical professionals and communicate credibly without oversimplifying clinical, operational, or regulatory constraints. Experience evaluating AI systems using both technical metrics and expert judgment, including cases where ground truth is noisy, incomplete, or context dependent. Strong understanding of trustworthy AI practices, and how to design provenance, access control, and uncertainty handling directly into a working system. Excellent written and verbal communication across engineering, scientific, clinical, quality, and executive audiences. Evidence of leading cross‑functional delivery through influence, including prioritization, conflict resolution, and shipping decisions under ambiguity. Desirable Skills/Experience Direct experience with clinical trial conduct, site monitoring, risk‑based monitoring, medical monitoring, clinical data review, or trial technology in a pharmaceutical, biotech, CRO, or health‑system environment. Working knowledge of GCP and GxP computerized-system validation, and how to scope a feature for regulated versus non‑regulated use before it is built. Experience with clinical systems and data such as CTMS, EDC, eTMF, safety systems, EHR, monitoring reports, or clinical data platforms. Experience designing reusable product capabilities across multiple therapeutic areas, studies, or business units. Familiarity with observability, LLMOps/MLOps, and production monitoring for deployed AI systems, and how evaluation results feed release decisions. Publications, patents, open‑source contributions, or a record of shipping technically differentiated AI products. The annual base pay for this position ranges from $144,648.8 to $216,973.2 USD . Our positions may be eligible for various incentives, including short‑term incentive bonuses, equity‑based awards for salaried roles, and commissions for sales roles. Benefits may include qualified retirement programs, paid time off—including vacation, holidays, and leave—as well as health, dental, and vision coverage, in accordance with the terms of the applicable plans. AstraZeneca is an equal opportunity employer committed to diversity and inclusion and to providing a workplace free from discrimination. AstraZeneca is committed to accommodating persons with disabilities. Accommodation is available upon request for all aspects of the recruitment, assessment, and selection process. Requests may be made by emailing View email address on click.appcast.io . Why AstraZeneca Join a technology‑powered organization where your AI leadership directly shapes how life‑changing medicines reach patients. Here, unexpected combinations of experts come together to tackle problems end to end—data foundations, AI models, platforms, and business applications—so your work moves from idea to enterprise scale. You will be empowered to take ownership, explore bold approaches, and push boundaries through hands‑on experimentation, including hackathons and large‑scale data challenges. We blend ambition with support: kindness matters as much as rigor; learning, coaching, and feedback are part of our daily rhythm; and every contribution is tied to a purpose bigger than any single team. This is a place to build trustworthy AI in partnership with clinicians and engineers, using cutting‑edge tools while keeping patient impact front and center. Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form. #J-18808-Ljbffr AstraZeneca plc