AI Engineer - Remote (Spain)

About the Role As an AI Engineer at Lifebit, you will be at the forefront of bridging massive, decentralized biomedical datasets and life-saving insights within our federated AI platform. You will build AI that operates inside a privacy-preserving, distributed environment and own the development and deployment of ML models—from LLMs for clinical note extraction to predictive analytics for genomic research. What You'll Do

• Design and implement autonomous AI agents using frameworks like LangGraph, CrewAI, or AutoGen to handle complex, multi-step scientific queries.
• Develop sophisticated reasoning loops (e.g., ReAct, Plan-and-Execute) to decompose high-level research goals into actionable sub-tasks.
• Build and optimize Advanced RAG (Retrieval-Augmented Generation) pipelines that integrate structured clinical data and unstructured literature.
• Create and maintain tools for AI agents to safely interface with Lifebit’s federated APIs, SQL databases, and bioinformatic execution engines.
• Implement secure, sandboxed code-interpreter capabilities, enabling agents to write and execute Python or R code for data visualization and statistical analysis.
• Fine-tune LLMs for function-calling and tool-use accuracy within life sciences.
• Develop evaluation frameworks (LLM-as-a-judge) to measure agentic performance, truthfulness, and safety in clinical contexts.
• Implement Human-in-the-Loop patterns to ensure high-stakes decisions are reviewed by domain experts.
• Partner with Security teams to ensure agents operate within strict data privacy boundaries, preventing prompt injection or unauthorized data egress in federated nodes.
• Collaborate with Product and UX teams to design intuitive interfaces for interacting with agentic systems and scale workloads in production using Kubernetes for low-latency reasoning. What We're Looking For
• Education: BSc/MSc in Computer Science, Artificial Intelligence, ML, or a highly quantitative field (PhD preferred).
• Experience: 2+ years as an AI/ML Engineer delivering a validated product in biotech/health-tech or SaaS.
• Technical Stack: Deep proficiency in Python and TypeScript; experience with PyTorch, TensorFlow, JAX, Scikit-learn; Langfuse.
• NLP/LLM Expertise: Proven experience with LLMs, fine-tuning, and RAG architectures.
• Cloud & Infrastructure: Familiarity with AWS/Azure/GCP; deploying models in Docker/Kubernetes.
• Domain Knowledge: Bio/genomics/clinical data experience is a significant advantage.
• Autonomy: Self-starter who can navigate ambiguity and drive AI projects from concept to production without constant oversight. Nice to Have
• Experience working with biological, genomic, or clinical data is a strong advantage.
• Familiarity with federated learning or privacy-preserving ML approaches. Compensation & Benefits
• Compensation: Competitive salary with performance-based incentives.
• Professional Development: £1,000 annual personal development budget and access to conferences, training, and certifications.
• Flexible Working: 21-25 days annual leave and fully remote.
• Diverse Team Culture: International and diverse team.
• Deep Technology & Science: Exposure to cloud, data analysis, ML, life sciences, and big data problems.