Senior Technical Specialist

Flexsis is a company of the Interiman Group, one of the leading providers of personnel services in Switzerland. Thanks to our solid expertise as well as the competencies within the Interiman Group, we offer tailored solutions in personnel consulting.

For our client Roche in Basel
, we are looking for a reliable and motivated (m/f/d)

• Start Date:
  
  Asap
• Latest Possible
  
  Start Date:
  
  04.01.2027
• Planned Duration of Employment: 12 months
• Extension:
  Rather Unlikely
• Workplace:
  Basel

• Design and deploy sophisticated agentic workflows using frameworks such as Lang Graph, CrewAI, or Auto Gen 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.

• 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 Lang Graph, CrewAI, Auto Gen, or Llama Index
• Solid experience with modern data engineering (SQL/No
  
  SQL, 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

• Master’s or PhD in Computer Science, AI, or a related quantitative field
• Experience in a highly regulated industry such as Healthcare, Fin Tech, or Aerospace
• Understanding / Showcasing practical, end-to-end implementation of security frameworks in complex agentic workflows
• Understanding of clinical trial life cycles and data standards
• Familiarity with monitoring tools for system performance, workflow analytics, and MLOps/Dev Ops best practices