Principal Data Scientist - AI
What you'll be doing
- You will explore and implement RAG or Graph RAG approaches to improve retrieval quality and reasoning in LLM workflows, including graph construction, entity linking, and hybrid scoring strategies.
- Design and implement LLM-powered systems that support multi-step task automation, tool use, and context-aware reasoning within the product.
- Contribute to prompt design and evaluate prompts results
- Design and implement MLOps pipelines with best practises in mind
- Prototype, evaluate, and ship AI features using platforms like Claude or Amazon Bedrock with a focus on production readiness, not just experimentation.
- Develop evaluation frameworks for testing model output quality, reliability, and alignment with user goals (e.g., hallucination detection, prompt regression, safety scoring).
- Work closely with engineers and designers to embed AI capabilities into real user workflows, ensuring that technical architecture supports meaningful product outcomes.
- Own the full lifecycle of AI components from evaluation frameworks, planning and modeling to testing, deployment, and continuous improvement.
- Contribute to our AI strategy and roadmap, helping shape how we scale LLM usage responsibly across the platform. You bridge product and engineering by embedding AI into user-facing features, not just prototypes.
- Collaborate closely with Principal Engineer to align AI workflows, system prompts, and model interaction layers.
- You're a practical AI builder. Not just a theorist. You think in terms of customer value, vs. research or academic novelty.
- You've worked with Claude and/or Amazon Bedrock (or similar LLM platforms) and understand prompt design, model behavior tuning, and output evaluation.
- You're comfortable writing code, reviewing PR's, and deliver a reliable, explainable, production-ready product.
- Are excited about MLOps and brings experience in implementing MLOps best practices.
- You're curious about how people interact with AI and want to build systems they can trust and understand.
- Experience fine tuning models.
- Ability to reason about multi-hop question answering, graph traversal, and integrating structured retrieval with LLM prompts.
- Performance over time.
- 5+ years experience in applied AI, machine learning systems, or data science roles with production responsibility.
- Proficiency in Python, with experience building and maintaining AI systems, not just analyses.
- Experience working in Java or TypeScript environments beneficial.
- Experience with Claude, OpenAI, Bedrock is nice to have or experience with similar LLM platforms required.
- Familiarity with RAG, Graph-based retrieval, prompt design, and multi-hop reasoning.
- Experience deploying LLM-powered features into production environments.
- Bonus: experience in vector stores, agent orchestration, or legaltech domain knowledge.
- Contributory pension plan.
- 26 days annual holidays, hybrid working, and length of service entitlement.
- Health Insurance.
- Loyalty Share Scheme.
- Enhanced Maternity and Paternity.
- Employee Assistance Programme.
- Electric Vehicle Salary Sacrifice.
- Cycle to Work Scheme.
- Calm and Mindfulness sessions.
- A day of leave to volunteer for charity or dependent cover.
- Accessible and modern office space and regular company social events.
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