Senior Technical Specialist (m/f/d)

Hays Basel, Schweiz

Gepostet vor 6 Tagen Befristet Competitive

Aufgaben

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

Profil

Experience and a Bachelor's or advanced degree in Computer Science, Machine Learning, Engineering, or Biomedical Informatics
Experience delivering AI/ML solutions as well as 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; experience with other programming languages (e.g., C#, Java, JavaScript, R, RShiny) is considered an advantage
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
Fluency in English
Nice to have: experience in a highly regulated industry such as Healthcare, FinTech, or Aerospace OR understanding of clinical trial life cycles and data standards
Nice to have: familiarity with monitoring tools for system performance, workflow analytics, and MLOps/DevOps best practices
Nice to have: experience to architect scalable solutions in complex environments with multiple existing system integrations