Fullstack Engineer with advanced AI orchestration (EN speaker)

Descrizione del posto

Are you a strategic, forward-thinking engineer who thrives at the intersection of full-stack engineering, advanced AI orchestration, and real-world scientific impact? If yes, this opportunity is for you! General Information: Start Date: Asap Latest Possible Start Date: 04.01.2027 Planned Duration of Employment: 12 months Workload: 100% Home Office: No Working Hours: Standard Tasks & Responsibilities: Design and deploy sophisticated agentic workflows using frameworks such as LangGraph, CrewAI, or AutoGen to automate complex clinical data management tasks. Build collaboration systems where specialised agents (e.g., Planner, Validator, and Protocol Reviewer) resolve end-to-end data challenges through high-quality, testable code and CI/CD pipelines. Apply systematic prompt engineering techniques (including Chain-of-Thought, ReAct, and Reflection) to guarantee high-fidelity outputs in a clinical context. Deploy AI agents into our cloud environment (AWS) while building and enhancing scalable applications that capture, move, and prepare scientific data. Partner with Data Integrity and Quality teams to ensure all agentic decisions are traceable, reproducible, and fully compliant with regulatory standards. Create reliable "Human-in-the-loop" (HITL) workflows and tool-calling agents to solve complex, highly regulated data challenges. Must Haves: 5+ years' experience and a Bachelor's or advanced degree in Computer Science, Machine Learning, Engineering, or Biomedical Informatics, alongside 8+ years of experience delivering AI/ML solutions plus 3+ years in full-stack software and data engineering Deep proficiency in Python and hands-on experience with AI orchestration frameworks like LangGraph, CrewAI, AutoGen, or LlamaIndex Solid experience with modern data engineering (SQL/NoSQL, APIs), Vector Databases (e.g., Chroma, Pinecone), and optimizing RAG pipelines Strong experience deploying AI systems on AWS, containerization (Docker, Kubernetes), CI/CD pipelines, Git, and service observability (logging, tracing, metrics) A strong understanding of model reproducibility, interpretability, and validation best practices within highly regulated environments Excellent problem-solving capabilities with the ability to explain complex technical concepts clearly to diverse global stakeholders Fluency in English We thank you for your application! Moutusi Chattopadhyay