JobdescriptionAre 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 InformationStart Date: AsapLatest Possible Start Date: Planned Duration of Employment: 12 monthsWorkload: 100%Home Office: NoWorking Hours: StandardTasks & ResponsibilitiesDesign 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 Haves5+ 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 engineeringDeep proficiency in Python and hands-on experience with AI orchestration frameworks like LangGraph, CrewAI, AutoGen, or LlamaIndexSolid experience with modern data engineering (SQL/NoSQL, APIs), Vector Databases (e.g., Chroma, Pinecone), and optimizing RAG pipelinesStrong 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 environmentsExcellent problem-solving capabilities with the ability to explain complex technical concepts clearly to diverse global stakeholdersFluency in EnglishWe thank you for your application!Moutusi Chattopadhyay #J-18808-Ljbffr
Fullstack Engineer with advanced AI orchestration (EN speaker) in Basel Arbeitgeber: Randstad (Schweiz) AG, c/o Johnson & Johnson
Die pRandstad (Schweiz) AG bietet Ihnen als Lagermitarbeiter in Schwarzenbach nicht nur eine spannende Tätigkeit in einem dynamischen Team, sondern auch ein unterstützendes Arbeitsumfeld, das auf Flexibilität und Zuverlässigkeit setzt. Unsere Mitarbeiter profitieren von einer positiven Unternehmenskultur, regelmäßigen Schulungen zur persönlichen Weiterentwicklung und attraktiven Arbeitszeiten, die eine ausgewogene Work-Life-Balance fördern.
Kontaktdaten:
Randstad (Schweiz) AG, c/o Johnson & Johnson Recruiting-Team
