About the Role Join a stealth healthtech startup founded by an ex-Google engineer, building AI tools that empower clinicians to make faster, evidence-based decisions at the bedside.
We’re developing a cutting-edge platform that combines LLMs, retrieval-augmented generation (RAG), and vector search infrastructure to deliver real-time clinical insights. As the Founding Backend Engineer, you’ll play a critical role in shaping our backend systems, architecture, and engineering culture from the ground up.
What You’ll Do
Build scalable backend microservices in Python (FastAPI) to support RAG workflows and user queries
Develop and optimise vector search pipelines using tools like PGVector, Pinecone, or Weaviate
Design embedding orchestration and hybrid retrieval mechanisms
Implement evaluation frameworks (BLEU, ROUGE, hallucination checks) to monitor answer quality
Deploy production systems on GCP (Cloud Run, Vertex AI, BigQuery, Pub/Sub)
Own observability, IaC (Terraform), and CI/CD (GitHub Actions) pipelines
Collaborate with product, mobile, and clinical experts to ship weekly improvements
Ensure compliance with data privacy standards (GDPR, NHS DSPT)
Who You Are
~5+ years of backend experience (ideally with Python )
~ Proven track record delivering ML, search, or recommender systems at scale
~ Deep knowledge of embeddings, LLM-based retrieval, and vector similarity search
~ Hands-on with GCP (or AWS/Azure), Terraform, CI/CD, and observability
~ Strong communicator, product-minded, and thrives in fast-paced startup environments
~ UK-based and available to work 2–3 days per week in-office (London)
Bonus Points
Experience in healthcare, medtech, or clinical systems
Familiarity with MLOps tooling (MLflow, Kubeflow, Vertex Pipelines)