Associate Director, Clinical AI Translation & Solutions

Job Title: Associate Director, Clinical AI Translation & Solutions

Introduction to role:

About AISI 

AI Science & Innovation (AISI) sits at the centre of AstraZeneca’s R&D AI transformation within Enterprise AI Unit (EAI). Our remit is to build, buy, and deliver the AI models and agents that change pipeline outcomes across discovery, translational science, biomarkers, and clinical development, ultimately improve patients’ lives. 

The opportunity 

We are building an end-to-end Enterprise AI engine that unites data foundations, AI models, platforms, and business-facing applications to accelerate results across the value chain. Success comes from reusing what already works, sharing ideas across teams, and scaling impact rather than building in isolation. 

Role overview 

AstraZeneca is building an AI capability for Clinical Development that will improve how trials are designed, conducted, monitored, and analysed across Enterprise R&D Functions. We are hiring an Associate Director, Clinical AI Translation & Solutions to turn complex clinical-operational workflows into useful, measurable, and reusable AI solutions. 

The role sits in the Clinical AI Applied Science & Translation team and engages directly with clinical stakeholders, Engineering, and data teams to shape priorities, requirements, and delivery through AstraZeneca’s existing Engineering organization. 

This is a hands-on AI research and development role with a focus on applied-science and translation in the clinical space. You will work directly with clinical operations teams, CRAs, medical monitors, data owners, quality partners, and engineers to understand how work is actually performed, identify where AI can safely help, and translate that understanding into working software. You will prototype in code, make architecture and scope trade-offs with Engineering, and remain accountable through evaluation, deployment, adoption, and iteration. 

The initial focus will include agentic workflows for improving clinical operations, with the expectation that reusable patterns will scale across Clinical Development. The strongest candidate combines strong software and applied-AI judgment with the credibility and empathy to work alongside clinical professionals in a regulated environment.

Accountabilities:

• Own a portfolio of clinical AI workflows from discovery through deployment, adoption, and measurable benefit realization. 

• Observe workflows directly alongside CRAs, site-monitoring leaders, clinical operations, and medical stakeholders, converting pain points into clear product requirements, data contracts, acceptance criteria, and evaluation plans. 

• Build and iterate hands-on prototypes in Python and related technologies; contribute production code, review pull requests, inspect logs, reproduce failures, and work directly with engineers to resolve them. 

• Design agentic workflows that combine language models, deterministic services, enterprise tools, and human review, with clear evidence provenance, uncertainty handling, and fail-safe behaviour. 

• Make disciplined scope decisions that separate demonstrations from production releases and non-GxP workflows from regulated use. 

• Define outcome measures spanning technical performance, clinical usefulness, workflow quality, user adoption, cycle time, and operational impact. 

• Lead human-in-the-loop testing with clinical subject-matter experts and translate feedback into prioritized, testable product changes. 

• Work with data-product owners and platform teams to establish reliable access to clinical systems, documents, and structured data while protecting privacy and data integrity. 

• Partner with Quality, Regulatory, Privacy, Security, and R&D IT to embed GCP, GxP, validation, auditability, and lifecycle requirements from the outset. 

• Promote reuse of enterprise platforms, data products, agent components, and evaluation assets; identify when to build, buy, partner, or adapt an existing capability. 

• Communicate product decisions, evidence, risks, dependencies, and trade-offs clearly to technical teams, clinical leaders, and executives. 

• 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 [email protected].

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.

Call to Action:

If you are ready to lead hands-on, high-consequence AI that clinicians trust and engineers love—while creating reusable capabilities that move an entire enterprise—step forward and shape what’s next!

#LI-Hybrid

Date Posted

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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.