AI Engineer Clinical Data Science

We are looking for an AI Engineer to join our Data Science team, building AI-powered solutions for clinical data processing and analysis within a major pharmaceutical organization. You will design, develop and deploy generative AI systems that automate clinical reporting workflows, extract intelligence from documents, and accelerate data-driven decision making. This is a hands‑on engineering role — you'll be writing production code, not just building prototypes.

• Generative AI & Automation.
• Develop LLM‑powered automation tools for clinical reporting and document generation workflows.
• Build AI‑driven code generation pipelines and quality assessment frameworks.
• Design and implement human‑in‑the‑loop review workflows with feedback loops to continuously improve output quality.

• Research and evaluate emerging AI methods, frameworks, and techniques for specific tasks — e.g. comparing fine‑tuning vs zero‑shot approaches, assessing new document extraction tools, or trialling new agentic frameworks.
• Prototype and benchmark new approaches before recommending adoption.
• Stay current with a rapidly evolving field and bring new ideas to the team.

• Design and build multi‑agent systems for data workflows — agents that retrieve, generate, validate, and iterate autonomously.
• Implement agent orchestration using frameworks such as Google ADK, Lang Graph, or Lang Chain.
• Deploy and manage agents on Google Vertex AI.

• Build document processing pipelines (PDFs, Word/DOCX) — extraction, parsing, table detection, structure recognition.
• Design and build RAG pipelines grounded in source documents.
• Process, extract and transform data from unstructured and semi‑structured sources.

• Write clean, well‑tested, maintainable Python code following SOLID principles and recognised design patterns.
• Apply single responsibility, dependency inversion, and interface segregation in real codebases — not just theory.
• Write meaningful tests and maintain high standards across the team.
• Refactor and improve existing code as part of normal development workflow.

• Use AI coding tools (e.g. Gemini CLI, Git Hub Copilot) as a core part of your development workflow.
• Critically review and validate AI‑generated code — understanding what it produces, why, and when it's wrong.
• Write effective prompts to direct AI tools toward correct, secure, well‑structured output.
• Know when to use AI and when to write code manually — judgement over speed.

• Integrate and orchestrate LLM providers available through Google Vertex AI (Gemini, etc.).
• Build internal tools and applications using Streamlit and FastAPI.
• Containerize and deploy services using Docker.

• MSc in Data Science, Computer Science, Bioinformatics, or related field (or equivalent practical experience), Strong Python skills.
• Hands‑on experience building RAG systems or LLM‑powered applications (using Lang Chain, Llama Index, or similar frameworks).
• Experience integrating LLM APIs (Google Gemini, OpenAI, or similar) — we work primarily through Google Vertex AI.
• Working knowledge of vector databases (Chroma
  
  DB, Weaviate, Qdrant, Pinecone, or similar).
• Cloud platform experience (GCP preferred, especially Vertex AI).
• Docker and containerised deployments.
• Strong software engineering fundamentals — SOLID principles, clean code practices, design patterns, testing, version control (Git), code review.
• Comfortable using AI‑assisted development tools (e.g. Gemini CLI, Git Hub Copilot) — and critically evaluating what they produce.
• Strongly Preferred.
• Experience with agentic AI patterns — multi‑agent orchestration, tool use, autonomous workflows (Lang Graph, Google ADK, or similar).
• Document processing experience — extracting and parsing data from PDFs and Word/DOCX files programmatically.
• Understanding of LLM evaluation principles and output quality assessment (BLEU, ROUGE etc, code execution metrics, or similar).
• Data science fundamentals — Pandas, Num Py, scikit‑learn, statistical analysis, data visualization.
• Prompt engineering and optimisation…