Fullstack Engineer with advanced AI orchestration
Vor 3 Tagen
Basel, Basel-Stadt (Kanton), Schweiz
InGoedeBanen.nl
Vollzeit
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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
* 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