73 jobs for “rag”
Tenth Revolution Group London £80,000 – £90,000 pa
This role involves designing and scaling Azure Databricks-based data platforms, building robust data pipelines, and developing AI and LLM-powered capabilities. You will work closely with Product, Engineering, and Business stakeholders to deliver data products that support commercial decision-making and optimize cloud environments for performance and cost.
Morson Edge West Yorkshire £170,000 – £180,000 pa
A senior leadership role owning the data and AI strategy, roadmap and technical direction across the organisation. Day to day it spans hands-on work with generative AI, LLMs, RAG and agentic architectures, MLOps and data platform governance, plus building and leading a high-performing Data & AI team and partnering with Product, Engineering, Architecture and Security to scale prototypes into production.
Aveni United Kingdom
Hands-on full-stack role building and shipping production AI products that integrate LLMs, RAG and agentic workflows into financial services processes. You own features end-to-end across Node.js/TypeScript microservices, React frontends and AWS cloud infrastructure, with a focus on evaluation, observability, reliability and mentoring engineers.
Maxwell Bond Gateshead £85,000 – £95,000 pa
Hands-on technical leadership role owning AI development for a product-led platform, taking LLM-powered features from concept to production. Involves architectural decisions on LLM integration, retrieval systems, model selection, plus AI evaluation, monitoring, security and cost management, while mentoring engineers. No direct reports initially.
Maxwell Bond London £150,000 – £175,000 pa
Hands-on role building LLM agent and retrieval systems on a small UK core team, reporting to the Head of Engineering. Work spans LangGraph/LangChain workflows, RAG pipelines with Qdrant and GraphRAG on Neo4j, model integration across Anthropic, OpenAI and Bedrock, plus evaluation harnesses and observability. Token cost, latency and auditability are treated as engineering constraints throughout.
Multiverse London
Leads the Diagnose & Prescribe engineering team, owning delivery, technical direction and team health across AI-heavy services for learner diagnosis, eligibility and recommendations. Stays hands-on with distributed designs, RabbitMQ event schemas, API contracts and production code while carving logic out of a legacy monolith into dedicated services.
Appcast Enterprise London
Builds and deploys production-grade AI applications and services, working across the full lifecycle from ideation and architecture to deployment and automation. Involves integrating LLMs, vector databases, RAG patterns and AI agents into scalable platforms, with a strong emphasis on CI/CD, testing, observability and cloud-native design in cross-functional embedded teams.
Acorn by Synergie Crewe
Design, build and deploy AI agents and autonomous workflows powered by GPT and other LLMs, connecting APIs, webhooks and business platforms into automated ecosystems. Build multi-step reasoning workflows, rapidly prototype new solutions and optimise them for performance, working with technical and commercial teams in a remote-first, fast-moving environment.
eFinancialCareers London
Join a newly formed innovation team at a global investment manager, building AI-powered products used by thousands of employees. You'll develop full stack applications in React and Python, integrating LLMs, RAG and AI agents into enterprise tools, and work with product managers and data scientists to ship production-ready solutions.
eFinancialCareers London
This role involves designing and delivering end-to-end agentic AI and LLM-based solutions for a leading investment house. You will work closely with business stakeholders to understand workflows, prototype AI systems, and integrate these solutions into existing enterprise systems, focusing on rapid delivery and measurable business impact.
Advancing People Brussels, Belgium
Builds and maintains Python-based Intelligent Document Processing pipelines, focusing on AI-driven document understanding such as data extraction and classification. Works in a product team alongside AI, front-end and infrastructure engineers, using LLMs, Flask/Django/FastAPI and cloud infrastructure. Requires two days per week in the Brussels office.
Ocado Kraków, Poland
Senior ML engineer role in a cross-craft data science team building prediction, ranking and personalisation systems for an e-commerce platform. Owns the full ML lifecycle on production systems, from experimentation and training through serving, monitoring and MLOps, while coaching others and shaping reusable platform building blocks.
eFinancialCareers Belfast
Operational role on Citi's Offensive Security and Vulnerability Management team, running penetration tests, vulnerability assessments and Red Team adversarial evaluations across the application portfolio. The AI dimension is twofold: testing GenAI applications and agentic systems for prompt injection, retrieval poisoning and tool misuse, while using AI-assisted tooling to speed up reconnaissance and validation. Involves building triage pipelines and containment architectures for AI agents at enterprise scale.
