Senior AI Engineer

We have a hugely exciting opportunity for a Senior AI Engineer who will take HealthHero's AI initiatives from prototype to production.

Your first project will be our flagship, the Clinical Brain: a system that includes a Class II medical device, with an AI layer interacting with deterministic components. You will work on it directly with the Director of Clinical Products and the Head of Quality & Compliance, so you will need to be comfortable building to the rigour, safety, traceability and documentation that a regulated medical device environment requires.

This is a cross-functional role, working across Data, Product, Engineering, Clinical, Operations and Customer Service teams. You will collaborate closely with Engineering and Data Platform team to build scalable AI capabilities, and with Data Scientists and clinical experts to design robust evaluations and ensure the quality, reliability and safety of AI solutions. Your key stakeholders will be the Head of AI Products, and, on the Clinical Brain, the Director of Clinical Products and the Head of Quality & Compliance.

You will own the technical delivery of AI initiatives end to end, from designing solutions and making architectural choices to building, evaluating and deploying them into production. You will also contribute to shaping our AI engineering practices and technical roadmap.

Your work will give clinicians time back, help patients access the right care faster, and make our teams more efficient, while maintaining the highest standards of clinical quality, patient safety and data protection.

About the role

Drive AI strategy and technical leadership

• Partner with Product, Data, Engineering, Clinical and Operations teams to identify, scope and evaluate AI opportunities.

• Challenge requirements and technical approaches, assess feasibility, business value and costs, and help prioritise high-impact initiatives.

• Contribute to the AI roadmap, architectural decisions and technology choices, while helping define AI engineering best practices and sharing expertise across teams.

Your first project: the Clinical Brain

The Clinical Brain is our flagship project and will be your first priority. It is a system that includes a Class II medical device, with an AI layer interacting with deterministic components, and you will build it hand in hand with the Director of Clinical Products, the Head of Quality & Compliance and the Head of AI Products. You will:

• Abstract patient intent: turn free-text and conversational patient input into structured, clinically meaningful intents.

• Condense and cluster questionnaires: reduce and group clinical questionnaires while preserving clinical meaning and safety.

• Combine NLP, LLMs and machine learning: design the AI layer and its interfaces with the deterministic components so that every output is traceable and explainable, with patient safety built in.

• Optimise the clinical graph: improve the structure and performance of the knowledge graph that underpins the Clinical Brain.

• Work with the Director of Clinical Products to translate clinical needs into AI behaviour, and to design and run clinical validation.

• Work with the Head of Quality & Compliance to meet Class II medical device requirements: design documentation, risk management, change control and traceability from requirement to test.

Evaluation

Evaluation is the backbone of the Clinical Brain and of every AI feature we ship. Building on the existing practices of our Data Scientists and clinical experts, you will:

• Golden datasets: curate and maintain reference datasets with clinicians, covering common cases, edge cases and safety-critical scenarios.

• Mixtures of evaluators: go beyond a single LLM-as-judge by combining multiple judges, calibrating them against clinician review and measuring inter-rater agreement.

• Human-in-the-loop review: design efficient clinician review workflows that feed back into datasets, prompts and models.

• Regression testing: automate evaluation so that every prompt, model or data change is gated before release.

• Evidence for regulation: produce evaluation evidence that supports the Class II medical device documentation within the Clinical Brain, and monitor performance and safety once in production.

Further opportunities

Alongside and after the Clinical Brain, you will have the opportunity to lead other AI initiatives, including:

• AI Medical Note Taker: develop and integrate AI-powered clinical documentation into our consultation products, working with clinicians to ensure accuracy, reliability and clinical safety.

• Contact Centre AI (CCaaS): build and integrate call and chat summarisation, intent detection and routing, agent assist and self-service flows into our contact centre platform.

• AI-powered automation: design and deploy operational and clinical-admin workflows using tools such as n8n, with LLM steps, error handling, monitoring and clean handover to business teams.

• Knowledge graphs and RAG: develop knowledge graph capabilities using technologies such as Neo4j, Cypher and GraphRAG to ground LLM answers in trusted, structured data.

• AI agents and MCP: build secure Model Context Protocol services that enable AI agents to interact with healthcare systems, including searching appointment availability and booking teleconsultations, with authentication, consent, audit logging and safe failure modes.

• Self-hosted LLMs: benchmark open-weight models and serving stacks (e.g. vLLM, TGI) against hosted APIs on latency, throughput, cost and quality, and recommend where self-hosting makes sense.

• Product integration: integrate AI services into our TypeScript and .NET products and APIs alongside Product Engineering teams.

Ensure AI quality, scalability and safety

• Collaborate with Engineering and Data Platform teams to build scalable, reusable AI capabilities.

• Industrialise LLMOps, including prompt versioning, observability, cost tracking and quality monitoring.

• Build AI components fit for a Class II medical device environment: work within our quality management system and regulated software lifecycle, contribute to clinical risk management, and maintain design documentation and...