(Lead) Research Engineer, Computing & Intelligence, IAIC

Research Engineer (Reusable Healthcare AI Assets)

The role will support the development, adoption, and continuous improvement of reusable AI assets and platforms through ecosystem engagement, platform operations, product thinking, and practical UI/UX capability.

Responsibilities

The successful candidate will work closely with researchers, engineers, product owners, healthcare and public‑sector stakeholders, and industry partners to identify user needs, translate them into actionable platform requirements, and drive the adoption of reusable AI assets. The role is suitable for someone who can engage stakeholders effectively, structure feedback into product and operational priorities, and contribute to simple, intuitive user journeys, wireframes, prototypes, dashboards, and documentation for AI platforms.

Requirements

Experience in at least one of the following areas: AI/ML platform delivery, product or platform operations, technical project management, ecosystem or stakeholder engagement, developer relations, digital transformation, UI/UX design, or technology adoption.

Working understanding of AI/ML systems, data‑driven applications, software platforms, APIs, cloud environments, MLOps, or reusable software/assets. Deep research specialisation is not required, but the candidate must be comfortable working with technical teams.

Ability to translate between domain needs, user pain points, operational constraints, and technical implementation requirements.

Practical exposure to user research, journey mapping, wireframing, prototyping, usability testing, information architecture, or interface review.

Strong written and verbal communication skills, with the ability to explain technical capabilities and trade‑offs to both technical and non‑technical audiences.

Good planning, coordination, and stakeholder management skills, with the ability to manage multiple workstreams independently in a fast‑moving environment.

Preferred Qualifications (one or more of the following)

Experience in healthcare, biomedical, public‑sector, or regulated digital systems.

Hands‑on experience with UI/UX or prototyping tools such as Figma, Miro, FigJam, Balsamiq, or equivalent.

Ability to build lightweight prototypes, demos, or dashboards using tools such as React, JavaScript/TypeScript, HTML/CSS, Streamlit, Gradio, Dash, Tableau, Power BI, or similar.

Experience managing reusable asset catalogues, platform onboarding journeys, technical documentation portals, design systems, knowledge bases, or developer‑facing resources.

Familiarity with agile delivery and collaboration tools such as Jira, Confluence, Git, GitHub/GitLab, or equivalent.

Awareness of responsible AI, model evaluation, AI safety, data privacy, cybersecurity, and governance considerations for AI systems.

The level of appointment will be commensurate with experience.

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