15 of 15 Retrieval-Augmented Generation Jobs in Berkshire

scalable AI services and data processing solutions using Python and related technologies. Build and maintain Retrieval-Augmented Generation (RAG) solutions and vector database architectures. Develop real-time AI applications, including speech-to-text and streaming AI interaction capabilities. Integrate AI capabilities with existing backend … technologies such as Pinecone, Weaviate, FAISS, or Azure AI Search. Experience building and supporting Retrieval-Augmented Generation (RAG) solutions. Experience working with OpenAI and other modern AI platforms. Expertise in prompt engineering, prompt evaluation, and optimisation techniques. Experience developing real-time AI and audio ...

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

systems in production environments, including performance tuning and cost optimization. Design and build Retrieval-Augmented Generation (RAG) systems using embeddings, vector databases, and semantic search. Build and optimize prompts and interaction strategies for LLMs to achieve desired outcomes in agentic systems. Integrate various tools … multi-agent systems. Familiarity with AI workflow orchestration and agentic frameworks (e.g., LangChain, LangGraph, Crew AI, Haystack, or similar). Practical experience with RAG architectures, embeddings, vector databases, and semantic search. Experience working with Model Context Protocol (MCP) Servers. Experience with RESTful APIs and integrating external services. Solid understanding ...

automated testing with pytest • Experience supporting and improving large, established production codebases, with a strong understanding of secure software development Experience with LangChain, RAG, vector databases, Azure, Entra ID, OAuth/OIDC, Redis, Terraform, Helm, Prometheus, Grafana or OpenTelemetry would be valuable but is not essential. Current SC clearance ...

cloud‐native delivery approaches Curiosity about AI‐enabled systems and how they scale responsibly Experience with LLMs, AI agent orchestration, or tools such as RAG, vector databases or LangChain is a bonus, but not essential. What's in it for you Flexible hybrid working 25 days leave, 2 days paid ...

API. Proven track record of delivering production software on client-facing projects, ideally within a consultancy or professional services environment. Experience with prompt engineering, RAG architectures, or agentic AI development at scale. Familiarity with AI-assisted development tools such as GitHub Copilot, Claude, and Cursor. Strong experience with Azure cloud ...

working closely with engineering, cloud and security teams to define practical controls and secure-by-design patterns. This will include areas such as LLMs, RAG, AI agents, vector databases, prompt injection, data leakage, identity, tool/API integration and AI threat modelling, alongside broader cloud and enterprise security architecture. ...

complex or ambiguous cross-functional operational challenges where requirements are not fully formed. Understanding of AI concepts (e.g. prompt engineering, retrieval ‐ augmented generation). Experience with system integration, APIs and data connectivity. Strong stakeholder engagement skills, with the ability to translate technical solutions into ...

practice Basic Qualifications Engineering experience with cloud-native systems (APIs, microservices, containerization, serverless). Deepexpertisein designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments. Experience with AI platforms OpenAI, Claude, Vertex AI, plus open-source models including building abstraction layers to manage multi-provider pipelines. ...

across a large enterprise. You will drive security architecture, enforce secure-by-design patterns and collaborate with engineering, cloud and security teams on LLMs, RAG, AI agents and data flows. The role is hybrid with bases in London or Reading. Visa sponsorship is available for candidates currently living ...

world enterprise use cases, driving POCs and transformation initiatives from concept to production. What You'll Do Design and build GenAI solutions using LLMs, RAG and prompt engineering Develop Agentic AI systems for automation and orchestration Build and deploy ML models for business use cases Work across AWS services including … years hands-on in AI/ML and GenAI Strong Python and Java skills Experience with LangChain, LlamaIndex, CrewAI or similar frameworks Knowledge of RAG, vector databases and semantic search AWS expertise (Bedrock and SageMaker preferred) Experience with APIs, microservices and cloud-native architecture Nice to Have AWS certifications ...

language model APIs across multiple providersAI coding tools: GitHub Copilot, Cursor or equivalentsPrompt engineering and context design patternsRetrieval-augmented generation (RAG), vector search, embeddings (desirable)Evaluation frameworks and automated quality pipelines for AI outputsTechnical and Professional ExpertiseSolid production experience with C# .NET, including working in established … improve quality. Daily fluency with AI coding tools such as GitHub Copilot, Cursor or equivalents. Preferred Qualifications and ExperienceRetrieval-augmented generation, agentic workflows, tool use, vector search or embeddings in production settings. Experience with LLM APIs across more than one provider, with a feel for their ...

language model APIs across multiple providersAI coding tools: GitHub Copilot, Cursor or equivalentsPrompt engineering and context design patternsRetrieval-augmented generation (RAG), vector search, embeddings (desirable)Evaluation frameworks and automated quality pipelines for AI outputsTechnical and Professional ExpertiseSolid production experience with C# .NET, including working in established … improve quality. Daily fluency with AI coding tools such as GitHub Copilot, Cursor or equivalents. Preferred Qualifications and ExperienceRetrieval-augmented generation, agentic workflows, tool use, vector search or embeddings in production settings. Experience with LLM APIs across more than one provider, with a feel for their ...

business value in a secure and scalable manner. Collaborate with senior stakeholders, design end-to-end Gen AI architectures, and develop reusable patterns for RAG, agent orchestration and knowledge retrieval. #J-18808-Ljbffr ...

Solution Delivery Lead the design, development and deployment of AI-integrated applications using modern full-stack technologies. Build features powered by LLMs, agentic workflows, RAG patterns and MCP integrations. Work directly with customers to shape requirements and translate them into working software. Integrate Azure AI services such as Azure OpenAI …/Node.js, .NET/C#, Python/FastAPI). Proven background delivering production software in client-facing environments. Experience with LLM integration, prompt engineering, RAG or agentic AI development. Familiarity with AI-assisted development tools (GitHub Copilot, Claude, Cursor). Hands-on experience with Azure cloud services and CI/ ...