AI Engineer

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Description

B2B contract , full-time, 12 months + extensions Working model: 100% remote We are looking for an experienced AI Engineer to design, build, validate and maintain production-grade LLM-based solutions for clinical and life-sciences use cases. The role combines hands-on GenAI engineering with strong Databricks, MLflow, LLM observability and GxP validation practices. You will work on AI solutions that require not only strong technical performance, but also traceability, reproducibility, documentation, controlled releases and audit readiness . Your responsibilities Designing, developing, validating and maintaining LLM-based solutions for clinical and life-sciences use cases. Building prompt workflows, RAG solutions, tool integrations, guardrails and human-in-the-loop mechanisms. Designing and maintaining knowledge graphs and graph-based AI solutions using technologies such as Neo4j. Building controlled end-to-end AI pipelines in Databricks . Supporting data ingestion, preparation, model integration, evaluation, deployment and monitoring. Integrating AI solutions with MLflow to capture: model and prompt versions, parameters, datasets, evaluation results, approvals, lineage, deployment records, associated technical artifacts. Using Langfuse for LLM observability, tracing and performance monitoring. Investigating unexpected model behaviour and supporting root cause analysis. Establishing end-to-end traceability across requirements, data, prompts, models, tests, approvals, releases an

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