9 of 9 Remote/Hybrid Retrieval-Augmented Generation Jobs in Berkshire

engineering best practices, delivery processes, and a high-performance team culture. Technical Ownership Lead architecture and development of LLM-powered and agentic applications, including RAG systems, chat/workflow agents, and domain-specific AI services. Drive technical direction with sound judgement and pragmatic decision-making. Build and deploy production-grade … systems into production. Deep expertise in: LLMs & transformer-based models Agentic frameworks (e.g., LangChain, LangGraph) Retrieval-Augmented Generation (RAG) Python Building or integrating LLMs into products or workflows Working with GenAI frameworks and tooling Designing or optimising prompt pipelines Deploying or supporting GenAI features ...

Architect & Engineer AI Systems: You won't just call an API; you will build robust processing architectures that leverage off-the-shelf LLMs, RAG pipelines, and context engineering to solve hard problems. You will benchmark these systems rigorously to ensure they actually work, not just \"feel\" smart. Build the Backend ...

strong parent-company backing. Key Responsibilities Design and deploy AI features (intelligent search, procurement agents, predictive maintenance). Build and integrate LLM-driven agents , RAG pipelines, and predictive models. Collaborate with software engineers to embed AI securely into production. Define AI standards , select tools, and shape the technical roadmap. Opportunity ...

handling both single-step LLM tasks and complex multi-step agentic workflows. As AI Engineer you will: Architect and implement the LLM, agentic and RAG modules that power the platform's low-code environment. Build primitives, abstractions and orchestration components that allow clients to construct robust agentic workflows with deterministic ...

autonomous AI What You'll Need: A strong foundation in data science and machine learning Hands-on use of modern AI tools (LLMs, RAG, LangChain, co-pilots, agentic workflows) Curiosity and eagerness to learn in a fast-moving AI landscape Experience collaborating with stakeholders and translating business problems into technical ...

NoSQL databases to build scalable, event-driven systems. Design and optimise APIs that serve our mobile and web products, including partner integrations. Implement efficient RAG AI backend systems for introducing advanced LLM based features Collaborate with product managers, data engineers, and frontend developers to deliver new features end to end. ...

looking for AI engineers who want to build production-ready AI solutions that tackle real-world challenges in life sciences, from RAG chatbots to agentic AI systems supporting evidence-driven projects. You will design, develop, and deploy AI systems that have measurable impact, influence patient access to treatments, and support … culture where employees can grow and make a tangible impact in healthcare. Key responsibilities Design, develop, and deploy AI systems with a focus on RAG chatbots and agentic AI. Lead real-world evidence projects, ensuring AI solutions are reliable, measurable, and impactful. Implement data pipelines, retraining workflows, and monitoring ...

Journey and broader Azure AI-related questions. Designing and delivering custom AI solutions on Azure OpenAI Service and Microsoft Foundry, using patterns like RAG, function calling, tool/agent orchestration, and fine-tuning where appropriate. Implementing MCP-based integrations between AI services and existing application components (web apps, APIs, data … Design and optimize data pipelines that prepare structured and unstructured data for model training and RAG solutions. Implement vector search, embeddings, and retrieval-augmented generation workflows. Fine-tune or customize foundation models for domain-specific use cases. Create automated evaluation and monitoring systems ...

grade RAG systems, knowledge orchestration, and agentic workflows. Their platform helps large organisations use their data more effectively through advanced retrieval augmented generation, intelligent automation, and high accuracy decision support. They are well funded and scaling their commercial function, and this is the first … engagement (10-18 months). Lead a top-down GTM strategy and position applied AI solutions to senior decision makers in financial institutions. Sell RAG based solutions, agentic workflows, and AI automation platforms into large organisations. Work closely with the CEO and CRO to shape commercial strategy, influence product direction ...