Technical Product Lead – Regulatory Innovation in Slough

We are seeking a hands-on, execution-focused Technical Product Lead – Regulatory Innovation to operate at the intersection of AI product development, clinical research, and regulatory strategy. This role is ideal for individuals with a technical foundation in AI/ML or software engineering who have evolved into product and regulatory leadership within life sciences. You will drive the development of fit-for-purpose, regulator-ready AI solutions used in clinical trials and clinical practice. A key focus will be enabling lean, scalable processes while advancing regulatory acceptance of novel AI methodologies. You will work cross-functionally across product, engineering, data science, clinical, and quality teams, and collaborate closely with regulatory stakeholders.

Key Responsibilities

• Lean Quality & Process Enablement
  • Partner with Quality to ensure the Quality Management System (QMS) is scalable, efficient, and minimally burdensome.
  • Embed quality and compliance into developer-native workflows.
  • Eliminate or refine controls that do not materially reduce risk.
  • Support teams in computerised system validation (CSV) from requirements definition through to validation and acceptance.
  • Provide pragmatic guidance, templates, and training on regulatory expectations without becoming documentation-driven.
  • Contribute to alignment across QMS, information security, and internal governance frameworks.
• Regulatory Innovation & Strategy
  • Monitor and interpret the evolving regulatory landscape for AI in healthcare and clinical trials.
  • Identify opportunities to apply innovative AI approaches within regulatory frameworks.
  • Translate internal innovations into regulator-ready evidence packages and methodologies.
  • Support and participate in regulatory engagement activities (e.g., scientific advice, workshops, industry forums).
  • Contribute to shaping emerging standards and expectations for AI validation and deployment.
• Product Leadership
  • Translate user needs, regulatory requirements, and scientific insights into clear product requirements and acceptance criteria.
  • Collaborate with engineering, data science, and clinical teams to define and prioritise the product roadmap.
  • Own the end-to-end product lifecycle, ensuring alignment across commercial, scientific, and regulatory objectives.
  • Define and manage stage-gates to ensure readiness for validation, release, and scaling.
  • Track product performance and user outcomes, driving continuous improvement.

Required Skills & Experience

• Degree in Engineering, Computer Science, or a related technical discipline.
• Significant experience in product ownership and regulatory environments, ideally within:
• AI-enabled healthcare software.
• Clinical trial systems.
• Regulated digital products.
• Strong understanding of quality, validation, and regulatory frameworks, such as:
• GxP / ICH-GCP.
• Computerised system validation (CSV / GAMP 5).
• ISO standards (e.g., 13485, 14971, 62304).
• Data integrity and electronic records requirements.
• Familiarity with emerging guidance on AI/ML in healthcare, including risk management and governance frameworks.
• Proven ability to design lean, scalable processes that support high-velocity product delivery in regulated environments.
• Technical fluency in AI/ML concepts, system architecture, and data pipelines.
• Strong analytical thinking and problem-solving skills.
• Ability to operate in cross-functional, fast-paced environments with a high degree of ownership.

Preferred Experience

• Experience within clinical trials (sponsor, CRO, or technology provider).
• Exposure to regulatory interactions, submissions, or advisory processes.
• Experience contributing to novel regulatory approaches or frameworks.
• Knowledge of information security standards (e.g., ISO 27001, SOC 2).
• Experience supporting regulated product submissions (e.g., CE marking, FDA pathways).

What We’re Looking For

• A hybrid thinker who can bridge technology, product, and regulation.
• A pragmatic, detail-oriented operator who prioritises execution over theory.
• Someone who challenges complexity and drives lean, outcome-focused processes.
• A confident communicator capable of engaging both technical teams and external stakeholders.

Working Environment

• Cross-functional, collaborative environment at the intersection of AI and life sciences.
• Opportunity to contribute to cutting-edge innovation in clinical research and healthcare.
• Hybrid working model (location flexible depending on organisation).