Key skills
AWSAzureCloudGoogle Cloud PlatformPythonAIOpenAIClaudeAnthropicRAGLlamaIndexAgenticAutoGenMLflowLangGraphPhoenixGCPGoogle CloudCommunication
About this role
Role Overview
- 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 agentic workflows capable of handling complex business processes.
- Build evaluation frameworks and observability capabilities that ensure reliability and quality.
- 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 AI solutions that create measurable value.
Requirements
- Strong Python skills and solid software engineering fundamentals.
- Hands-on experience with at least one major cloud (AWS, Azure, or GCP).
- Deep, hands-on experience with enterprise LLMs and their APIs (e.g. Anthropic/Claude, OpenAI, Google), including tool/function calling, structured outputs, and the Model Context Protocol (MCP).
- Experience building agentic systems with modern orchestration frameworks such as Pydantic AI, LangGraph, OpenAI Agents SDK, AutoGen / Microsoft Agent Framework, or LlamaIndex.
- Strong command of retrieval techniques including RAG and graph-RAG, vector search, embeddings, reranking, and document-processing pipelines.
- Practical context-engineering skills and the ability to consistently improve AI quality through prompt and context design.
- Experience with evals and observability as first-class concerns, including evaluation suites, tracing, regression testing, reliability, latency, and cost management.
- Familiarity with tooling such as LangSmith, Langfuse, Braintrust, Arize Phoenix, MLflow, DeepEval, or Promptfoo.
- A solid foundation in data science fundamentals, data analysis, and statistical thinking.
- Strong communication skills in English.
- Understanding of pharmaceutical clinical and regulatory documents and workflows (nice to have).
- Awareness of GxP, 21 CFR Part 11, GDPR, HIPAA, and computer system validation (nice to have).
- Experience with semantic computing and document structuring (nice to have).
- Experience deploying secure, compliant applications in regulated cloud environments (nice to have).
- Experience with life science upstream source systems such as Veeva (nice to have).
Tech Stack
- AWS
- Azure
- Cloud
- Google Cloud Platform
- Python
Benefits
- Support for health and wellbeing, covering physical, mental, and social needs
- Flexible ways of working, built on trust, autonomy, and balance
- Ongoing learning and professional development throughout your career
- A modern work setup, with the tools and equipment needed to do great work
- Recognition of performance and impact, linked to contribution and results