Director, Regulatory AI Business Partner

AstraZeneca•Cambridge, MA

3d•$186,014 - $279,022•Hybrid

About The Position

This role can be based at AstraZeneca hubs in Boston, US; Gaithersburg, US; Cambridge, UK or Barcelona, Spain. About AISI AI Strategy & Innovation (AISI) sits at the centre of AstraZeneca's R&D AI transformation. 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. Role Overview We are hiring a Director, Regulatory AI Business Partner to serve as the single, senior point of partnership between the AI for Clinical Development team as a front door to the Enterprise AI Unit, and the Regulatory function across the enterprise. You will deeply understand how this function works and what it needs, coordinate with ongoing digital, data science, and AI efforts within the function, translate and align that into a prioritized view of the Regulatory use cases where AI can add the most value, helping decide what is best delivered as a shared enterprise capability versus enabled within Regulatory itself—so we meet the needs of our Regulatory partners with measurable value. The role covers enabling Regulatory to deliver its own prioritized use cases, and shaping enterprise-level AI capabilities that Regulatory shares with other functions, and facilitating responsible and compliant AI in the context of clinical trial conduct, delivery, and reporting. You will sit between domain experts in Regulatory and AI engineers and scientists in EAI. You will interface closely with partners throughout the enterprise building enterprise-level capabilities spanning IT, data access and management, product, and software engineering. You will be equally comfortable in a conversation about regulatory submission standards and a conversation about data infrastructure, pipelines, and what it takes to make a model production- and audit-ready. Comfort with ambiguity, a bias for demonstrating value early, and the credibility to build trust with senior stakeholders across functions are core to the role.

Requirements

Master's degree in AI/ML, data science, health informatics, or a related field; an advanced degree is a plus. We welcome strong candidates from adjacent fields whose experience maps to the role.
5+ years of experience in digital health, AI/ML, or a technology-driven environment within healthcare or drug development, and meaningful exposure to Regulatory, with a demonstrated track record of identifying, articulating, and realizing the value of AI and data products in a real business setting.
Demonstrated stakeholder management ability, including building credibility with and influencing senior stakeholders across functions.
Ability to understand and reason about data, data and compute infrastructure, and pipelines, and to translate fluently between technical teams and business or domain audiences.
Comfort interfacing with IT and enterprise data functions on data access, governance, infrastructure, and compute.
Excellent interpersonal, verbal, and written communication skills, with the ability to operate in an international matrix environment and bring structure and clarity to ambiguous problems.
Comfort with ambiguity and a bias for action in a fast-moving, build-from-the-ground-up environment.
Familiarity with AI governance, compliance, and responsible-AI considerations in a regulated (GxP) environment, and the judgment to know when specialist input is required.

Nice To Haves

Hands-on experience in Regulatory Affairs within life sciences or at a Health Authority (e.g., FDA, EMA).
Direct, hands-on experience with Regulatory standards and workflows (regulatory submissions, regulatory affairs operations, and clinical data management) in drug development. Experience spanning both industry and Health Authority (e.g., FDA, EMA) settings is highly valued.
Familiarity with regulatory and clinical data standards and compliance
Experience with generative AI or agentic systems applied to regulatory writing and submissions.
Experience supporting buy-vs-build decisions, vendor evaluation, or AI/data product management.
Advanced degree (PhD, MD) in a relevant scientific, statistical, or technical field.
Clinical training or a clinical background (e.g., MD, PharmD, RN) that supports credible engagement with clinical and regulatory stakeholders.
Awareness of how AI-enabled tools and connected or digital health technologies (e.g., software as a medical device, wearables) can themselves fall under regulatory oversight.

Responsibilities

Serve as the primary, trusted business partner between AI for Clinical Development team and the Regulatory function across the enterprise.
Partner closely with AI for Clinical Development function leads and their teams, and the broader EAI teams, to develop AI solutions, sitting on project teams and where needed engaging Regulatory domain expertise directly into solution development, keeping delivery aligned to function needs.
Develop a deep, current understanding of Regulatory priorities, workflows, and decision points.
Understand and coordinate with ongoing digital and AI efforts within the Regulatory function.
Build credibility and trusted relationships with senior leaders across the function, and act as a calm, structured partner when priorities compete.
Connect with the digital, data science, and AI teams embedded within the Regulatory function and the therapy areas, and with senior Regulatory leaders across biopharma and oncology, so efforts are coordinated rather than duplicated.
Act as a bridge on responsible and compliant AI for the AI for Clinical Development team: flag early when a solution under development may constitute a regulated product or otherwise trigger regulatory requirements, and help teams chart a path through them.
Partner with compliance, quality, privacy, and data-governance stakeholders to close gaps where enterprise guidance does not yet exist, so teams can move quickly without taking on undue risk.
Provide AI expertise and consultation to Regulatory—advising where AI will add the most value within the function's digital roadmap, and how AI can support Regulatory in achieving its digitally-enabled vision.
Translate function needs into a prioritized, sequenced set of AI opportunities—drawing on Regulatory's existing roadmaps rather than a new list—and help decide which are best implemented at the enterprise level versus within the function directly.
Define and demonstrate the value of AI solutions for Regulatory: build the business case, agree success metrics up front, and track adoption and benefits realization after delivery.
Contribute the business and domain perspective to buy-vs-build and vendor-evaluation decisions for Regulatory use cases.
Help establish appropriate performance, cost, and latency expectations for shared clinical AI capabilities in partnership with the team's evaluation and monitoring efforts.
Coordinate related AI efforts to find shared, reusable solutions—so a single investment can meet common needs across functions rather than three parallel builds.
Maintain a current view of the external vendor and technology landscape relevant to Regulatory, so build-vs-buy and partnering decisions reflect the latest options.
Interface with IT and data teams to ensure that Regulatory AI solutions are aligned and implementable within data access, pipelines, compute, and infrastructure.
Understand clinical data and regulatory standards, data governance, and what it takes for a solution to operate in a validated, audit-ready, regulatory-grade environment.
Understand data and compute infrastructure and pipelines well enough to scope feasibility, identify dependencies and gaps, and broker solutions across technical and business teams.
Ensure solutions are designed from the start to meet the evidentiary, compliance, and data-integrity bar that Regulatory work requires.
Help teams identify solutions across the “last mile”—from a working prototype to a connected, productionized, and supported capability.
Contribute to the roadmap for AI across Regulatory, aligning efforts across the enterprise.
Partner with Regulatory to identify methodologic requirements, evidence gaps, and advocacy opportunities needed to safely advance clinical AI innovations.