Principal Data Scientist, AI

Opus 2

full-time

Posted on: 9/8/2025

Location: 🇬🇧 United Kingdom

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About the role

Lead the design of AI systems that support complex, multi-step tasks, tool use, context adaptation, and intelligent decisions.
Work closely with product and engineering to architect LLM-powered features that are robust, useful, and production-ready.
Explore and implement RAG or Graph RAG approaches, including graph construction, entity linking, and hybrid scoring strategies.
Design and implement LLM-powered systems for multi-step task automation, tool use, and context-aware reasoning.
Contribute to prompt design and evaluate prompt results.
Design and implement MLOps pipelines following best practices.
Prototype, evaluate, and ship AI features using platforms like Claude or Amazon Bedrock with production readiness focus.
Develop evaluation frameworks for model output quality, reliability, and alignment (e.g., hallucination detection, prompt regression, safety scoring).
Embed AI capabilities into user workflows with engineers and designers to ensure meaningful product outcomes.
Own the full lifecycle of AI components from evaluation and planning to testing, deployment, and continuous improvement.
Contribute to AI strategy and roadmap to scale LLM usage responsibly across the platform.
Collaborate closely with Principal Engineer to align AI workflows, system prompts, and model interaction layers.

Practical AI builder focused on customer value rather than academic novelty.
Experience with Claude and/or Amazon Bedrock (or similar LLM platforms) and prompt design, model behaviour tuning, and output evaluation.
Comfortable writing code, reviewing PRs, and delivering reliable, explainable, production-ready products.
Experience implementing MLOps best practices.
Curious about how people interact with AI and building trustworthy systems.
Experience fine tuning models.
Ability to reason about multi-hop question answering, graph traversal, and integrating structured retrieval with LLM prompts.
5+ years experience in applied AI, machine learning systems, or data science roles with production responsibility.
Proficiency in Python and experience building and maintaining AI systems.
Experience working in Java or TypeScript environments (beneficial).
Experience with Claude, OpenAI, Bedrock or similar LLM platforms.
Familiarity with RAG, Graph-based retrieval, prompt design, and multi-hop reasoning.
Experience deploying LLM-powered features into production environments.
Bonus: experience with vector stores, agent orchestration, or legaltech domain knowledge.