AI NLP Engineer

In this role you will work in the Platform team – a function for the deployment and evolution of the backend platform that underpins the core of the Xantura business. The Role You'll own and evolve Xantura's text analytics platform (XTA), the NLP system that extracts structured intelligence from unstructured case notes across health, housing, and social care. You'll work across the full spectrum of NLP: from classical text classification and entity extraction through to LLM-based information extraction, embedding models, and retrieval systems. As the platform matures, you'll help shape our agentic AI capabilities. Key Responsibilities Own and evolve the core text analytics pipeline; advancing large-scale concept extraction, classification, and information retrieval across complex social and clinical text corpora. Design and implement LLM-based processing chains for structured information extraction, leveraging prompt engineering, output parsing, and model orchestration to produce high-quality, auditable outputs at scale. Build and manage embedding infrastructure; training, fine-tuning, and serving embedding models, and setting up and operating vector databases to enable semantic search and retrieval across client data. Develop and maintain classical NLP components where appropriate; training smaller classifiers, entity recognisers, and domain-specific models for tasks where efficiency and interpretability outweigh generative approaches. Lay the groundwork for agentic AI capabilities as the platform evolves; contributing to the design of multi-agent orchestration, tool integration, and conversational interfaces over Xantura's services. Ensure all NLP systems are robust, explainable, and aligned with Responsible AI principles; essential where outputs inform decisions about vulnerable people in health and social care. Skills, Knowledge & Expertise Bachelor's or Master's degree in Computer Science, Computational Linguistics, Machine Learning, or a related technical field, or equivalent practical experience. 3+ years of professional experience in an NLP, ML, or AI engineering role Strong programming skills and production experience in Python. Clear evidence of practical experience across some or all of the following: LLM utilisation in production; prompt engineering, output structuring, chaining, and integrating LLMs into data processing pipelines (e.g. via LangChain, PydanticAI, or similar); Embedding models; training, fine-tuning, or serving embedding models (e.g. sentence-transformers, bi-encoders, cross-encoders), with practical experience setting up and managing vector databases (e.g. Qdrant, Weaviate, Milvus, pgvector) along with understanding trade-offs e.g. when to use sparse or dense embeddings (or both) etc; Classical NLP training and evaluating text classifiers, NER models, or other supervised/semi-supervised NLP models for domain-specific tasks. In addition, the following would be an advantage: Experience with knowledge graphs/triplestores/semantic web frameworks (e.g. Neo4j, RDF/SPARQL/OWL, Apache Jena). Practical experience with entity linking, concept normalisation, or ontology-driven NLP. Experience with retrieval-augmented generation (RAG) pipelines Familiarity with agentic AI frameworks and multi-agent orchestration (e.g. LangGraph, AutoGen). Good familiarity with the Azure ecosystem (Azure Kubernetes Service, Azure Container Registry, Azure DevOps, Azure Blob Storage, Azure Monitor, Azure Key Vault). This is a hybrid role based in our office in London (Borough). You would be expected to be able to work from the office at least 1-2 days per week. Some travel is required for on-site client engagements as needed. Job Benefits Competitive salary reviewed annually Work for a passionate, mission-driven company solving society’s big problems Work flexible hours around life commitments with a focus on delivering company value rather than hours worked Ability to work remotely (excluding face-to-face Team Meetings and client meetings) Training and development opportunities 25 days annual leave (plus bank holidays) Company pension Private medical insurance Generous enhanced parental leave policies Cycle to work scheme Flu Vaccinations, Eye Test and contribution towards Glasses for VDU use Employee Assistance Programme Mental health and wellbeing support Remote GP access Counselling/therapy Physiotherapy Medical second opinions