Lifebit

• As a Data Engineer, you will bridge the gap between complex biological science and robust software engineering. • You will be responsible for building the scalable infrastructure that powers our scientific discoveries. • Ensuring that our data pipelines are not only high-performing but also strictly compliant with European data protection standards. • Lead the implementation of challenging features across distributed architectures, ensuring systems are performant, maintainable, and secure. • Design software with built-in resilience and observability; balance immediate product delivery with long-term platform sustainability. • Convert complex scientific requirements into actionable engineering tasks for the development team. • Collaborate with Product, Science, and DevOps to define milestones and ensure projects move from conception to production with measurable impact. • Lead root cause analysis (RCA) for live incidents and implement permanent structural solutions.

• Lead the design and delivery of AI capabilities within a chat-based product interface. • Drive the strategy for data modeling, transformation, and standardization across the platform. • Drive the full product lifecycle within an Agile framework, leading cross-functional squads. • Own and plan product area’s roadmap, focusing on outcome-based goals. • Lead the integration of advanced user analytics and partner with Design and User Research teams. • Measure, track, and report on product KPIs to stakeholders, providing data-driven rationale. • Utilise Jira and Confluence as the "source of truth" for technical specifications. • Work closely with Legal and Clinical teams to ensure compliance with data residency requirements, GDPR, and international health data standards.

• 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) that allow agents 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 scientific literature. • Create and maintain 'tools' for AI agents, enabling them to safely interface with Lifebit’s federated APIs, SQL databases, and bioinformatic execution engines. • Implement secure, sandboxed code-interpreter capabilities, allowing agents to write and execute Python or R code for data visualization and statistical analysis. • Fine-tune LLMs for specific function-calling and tool-use accuracy within the life sciences domain. • Develop robust evaluation frameworks (LLM-as-a-judge) to measure agentic performance, truthfulness, and safety in a clinical context. • Implement 'Human-in-the-loop' (HITL) patterns to ensure high-stakes scientific decisions are always 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. • Work with Product and UX teams to design intuitive interfaces for interacting with agentic systems (e.g., conversational research assistants). • Scale agentic workloads in production using Kubernetes, ensuring low-latency reasoning and efficient token usage.

• Support Senior Solutions Managers and Sales in preparing demos, presentations, and technical documentation. • Participate in customer onboarding and platform setup activities, ensuring smooth handover and communication. • Work closely with senior team members to capture customer feedback and translate it into actionable insights for product and engineering teams. • Help configure data ingestion and harmonization pipelines (e.g., OMOP, FHIR, CDISC) under supervision. • Collaborate with clients and internal teams to learn how to design, configure, and communicate solutions.

• Support Senior Solutions Managers and Sales in preparing demos, presentations, and technical documentation. • Assist with solution workshops and proposal responses by gathering requirements and helping align them with Lifebit’s capabilities. • Participate in customer onboarding and platform setup activities, ensuring smooth handover and communication. • Help configure data ingestion and harmonization pipelines (e.g., OMOP, FHIR, CDISC) under supervision. • Shadow customer meetings and deployments to gain experience with federated access, metadata cataloging, and Trusted Research Environment (TRE) capabilities. • Work closely with senior team members to capture customer feedback and translate it into actionable insights for product and engineering teams. • Assist in preparing internal documentation, training materials, and user guides for customers. • Contribute to whitepapers or technical notes as part of your professional development.