Fullstack Engineer with advanced AI orchestration (EN speaker)

Jobdescription

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!