Design, build, and ship AI-powered tools that help life science teams create, review, and manage critical documents and data.
Build features such as grounded retrieval, summarisation, document comparison, question answering, and content classification with traceability back to source.
Design and implement scalable APIs, services, integrations, and deployment platforms.
Ensure solutions are secure, auditable, and scalable in regulated cloud environments (AWS, Azure, GCP).
Collaborate closely with clinical, regulatory, quality, and commercial experts to understand their workflows and implement products that solve real business problems.

Strong Python skills and solid software engineering fundamentals.
Hands-on experience with at least one major cloud (AWS, Azure, or GCP).
Strong software architecture and backend engineering experience, including production APIs and service design.
A track record of building robust, secure, scalable applications and integrating AI/LLM engines into them cleanly.
Comfort with containerisation (Docker, Kubernetes), CI/CD, infrastructure-as-code, and cloud-native deployment.
Experience designing for security, multi-tenancy, and auditability.
Working knowledge of databases and data engineering, including vector databases and vector search technologies.
Awareness of LLMOps practices for taking AI-based systems into production and operating them successfully.
Full-stack experience (e.g. TypeScript/React) is a plus but not required.
Strong communication skills in English.

AI Product Developer

Key skills