1 to 25 of 217 Remote/Hybrid Retrieval-Augmented Generation Jobs in England

learning and large language models (LLMs) using frameworks such as PyTorch, TensorFlow, and Keras. Develop Retrieval-Augmented Generation (RAG) applications using LangChain, Hugging Face, and LlamaIndex. Implement and optimize vector database, semantic search, and hybrid search solutions for AI-powered applications. Perform model fine … model repositories Proficiency in LangChain and LlamaIndex for building AI-powered workflows Experience implementing Retrieval-Augmented Generation (RAG) frameworks Knowledge of Vector Databases and Hybrid Search techniques Strong understanding of Natural Language Processing (NLP) concepts and applications Experience with data processing, transformation, and feature ...

solutions using modern Azure technologies and cloud-native architecture. Integrate Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and Agentic AI capabilities into business applications. Develop responsive frontend applications alongside robust APIs and backend services to create seamless user experiences. Work closely with Product … Services and cloud-native application development. Experience implementing AI solutions including LLM integration, prompt engineering, Retrieval-Augmented Generation (RAG) and vector databases. Experience working with SQL and NoSQL databases, with knowledge of platforms such as SQL Server, Snowflake, OneLake or similar data platforms. Strong ...

solutions using modern Azure technologies and cloud-native architecture. Integrate Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and Agentic AI capabilities into business applications. Develop responsive frontend applications alongside robust APIs and backend services to create seamless user experiences. Work closely with Product … Services and cloud-native application development. Experience implementing AI solutions including LLM integration, prompt engineering, Retrieval-Augmented Generation (RAG) and vector databases. Experience working with SQL and NoSQL databases, with knowledge of platforms such as SQL Server, Snowflake, OneLake or similar data platforms. Strong ...

solutions using modern Azure technologies and cloud-native architecture. Integrate Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and Agentic AI capabilities into business applications. Develop responsive frontend applications alongside robust APIs and backend services to create seamless user experiences. Work closely with Product … Services and cloud-native application development. Experience implementing AI solutions including LLM integration, prompt engineering, Retrieval-Augmented Generation (RAG) and vector databases. Experience working with SQL and NoSQL databases, with knowledge of platforms such as SQL Server, Snowflake, OneLake or similar data platforms. Strong ...

Engineer GenAI | RAG | AI Agents | Python | SQL Locations: Manchester, Leeds, Edinburgh (preferred) | Birmingham & Bristol considered - hybrid working - 2 days per week in either of the above locations Contract initially until Dec 2026. Day rate: up to £800 inside IR35 via umbrella The Opportunity We're looking for an experienced … business teams to deliver innovative AI solutions. Essential Skills & Experience Commercial experience building Generative AI solutions. Strong hands-on experience with RAG (Retrieval-Augmented Generation). Experience developing AI Agents or Agentic AI applications. Strong Python development skills. Strong SQL skills. Experience integrating applications ...

Engineer GenAI | RAG | AI Agents | Python | SQL Locations: Manchester, Leeds, Edinburgh (preferred) | Birmingham & Bristol considered - hybrid working - 2 days per week in either of the above locations Contract initially until Dec 2026. Day rate: up to £800 inside IR35 via umbrella The Opportunity We're looking for an experienced … business teams to deliver innovative AI solutions. Essential Skills & Experience Commercial experience building Generative AI solutions. Strong hands-on experience with RAG (Retrieval-Augmented Generation). Experience developing AI Agents or Agentic AI applications. Strong Python development skills. Strong SQL skills. Experience integrating applications ...

Experience designing multi-agent systems or autonomous workflows. Hands-on experience with Docker and deploying containerised, cloud-native tools. Experience with advanced retrieval-augmented generation techniques, including: TAG (Tool-Augmented Generation) – integrating external tools to enhance generation capabilities. … Context-Aware Generation) – leveraging dynamic context to improve relevance and coherence. GraphRAG (Graph-Augmented Retrieval-Augmented Generation) – utilizing graph-based structures to enrich retrieval and reasoning. This will include the competencies Stakeholder engagement: Works with cross-functional teams ...

Machine Learning solutions for customer-specific use cases. Build AI assistants, copilots, intelligent automation, and retrieval-augmented generation (RAG) applications. Design and integrate AI workflows with enterprise systems, databases, APIs, and business applications. Fine-tune prompts, optimize AI workflows, and improve model performance. Deploy … regulated industries such as Healthcare, Financial Services, Insurance, Telecom, or Manufacturing. Knowledge of AI governance, responsible AI, security, and compliance frameworks. Experience implementing RAG architectures and enterprise AI assistants. Exposure to AI observability, evaluation frameworks, guardrails, and monitoring platforms. Experience with Agentic AI and Multi-Agent Systems. Relevant certifications ...

language models across text, image, audio, and videoDesign and implement agentic workflows using prompt engineering, Retrieval-Augmented Generation (RAG), APIs, and enterprise data integrationsFine-tune, optimize, and deploy large language and multi-modal models with a focus on scalability, reliability, and low-latency performanceBuild … problem-solving skills within agile delivery environmentsBonus Points ForExperience building AI agent frameworks or autonomous orchestration platformsKnowledge of vector databases, semantic search, and advanced RAG architecturesExperience with cloud platforms such as AWS, Azure, or GCP for AI workloadsFamiliarity with financial services, banking, or regulated enterprise environmentsExposure to AI governance, model ...

tools such as LangChain, LlamaIndex, Hugging Face, and APIs from OpenAI and Anthropic. Building retrieval-augmented generation (RAG) prototypes with vector stores and knowledge graphs. Developing and testing agentic architectures through our own Genie Platform – enabling AI agents that reason, retrieve, and act across … language suited to AI system development and data workflows. Experience integrating models with APIs, data sources, or production systems. Curiosity about LLMs, RAG pipelines (Graph & Vector based), and agent frameworks. Understanding of cloud-native (AWS/GCP/Azure) and DevOps/DevSecOps practices. A collaborative mindset and willingness ...

tools such as LangChain, LlamaIndex, Hugging Face, and APIs from OpenAI and Anthropic. Building retrieval-augmented generation (RAG) prototypes with vector stores and knowledge graphs. Developing and testing agentic architectures through our own Genie Platform – enabling AI agents that reason, retrieve, and act across … language suited to AI system development and data workflows. Experience integrating models with APIs, data sources, or production systems. Curiosity about LLMs, RAG pipelines (Graph & Vector based), and agent frameworks. Understanding of cloud-native (AWS/GCP/Azure) and DevOps/DevSecOps practices. A collaborative mindset and willingness ...

hands-on AI & Data Engineer to design, build and productionise AI agents, automation solutions, Retrieval-Augmented Generation (RAG) capabilities and data products supporting Balance Sheet Modelling . The role will work closely with business, architecture and technology teams to translate business use cases into … Umbrella. Remote First Working - Travel to local site when required. Key Responsibilities Design, develop and deploy production-ready AI agents and agentic workflows. Build RAG solutions, integrating Large Language Models (LLMs) with enterprise data and knowledge sources. Apply prompt engineering techniques to improve the accuracy, reliability and effectiveness ...

effectively as part of their day-to-day workflow. Bonus points for: Experience with retrieval-augmented generation (RAG) and vector databases (pgvector, Pinecone, or similar).Experience designing multi-agent systems and agent orchestration patterns. Familiarity with LLM observability tools (LangSmith, Langfuse, Arize, or similar ...

deployment of GenAI solutions, including LLM-based applications, prompt engineering, fine-tuning, embeddings, and retrieval-augmented generation (RAG) for enterprise use cases. The ideal candidate has a strong foundation in machine learning and NLP, with hands‐on experience in modern GenAI tools and frameworks ...

architecture strategy and roadmap. Build scalable AI/ML and Agentic AI platforms spanning LLMs, retrieval-augmented generation (RAG), embeddings and semantic search. Lead on deployment, governance and integration patterns, advise clients on platform capability and implementation strategy, and partner with engineering, data, DevOps … business teams to deliver end-to-end solutions.**Tech environment**Python, LLMs (prompt engineering, fine-tuning, RAG), LangChain/LangGraph, agent frameworks, vector databases, MLOps/LLMOps, AWS, Azure, GCP, Databricks, Kubernetes and GPU infrastructure.**What we're looking for**Proven enterprise AI or ML architecture design, strong cloud ...

product) to identify high-impact opportunities for AI-driven automation and intelligent tooling Stay at the forefront of agentic AI research — including LLM orchestration, RAG, function calling, and autonomous code generation — and bring those advances into our platform Mentor engineers across the team on AI-first development practices … with modern LLM orchestration tools, prompt engineering techniques, and AI/ML frameworks Experience with retrieval-augmented generation (RAG), function/tool calling, and evaluation-driven development for AI agents A builder's mentality — you don't just use AI tools, you create autonomous ...

with the team to develop GenAI proof-of-concepts (POCs) for clients using technologies like Retrieval-Augmented Generation (RAG) and intelligent agents.* Scale existing POCs to production-ready solutions for customer use.* Design and develop FullStack applications for both GenAI and non-GenAI projects. ...

with the team to develop GenAI proof-of-concepts (POCs) for clients using technologies like Retrieval-Augmented Generation (RAG) and intelligent agents.* Scale existing POCs to production-ready solutions for customer use.* Design and develop FullStack applications for both GenAI and non-GenAI projects. ...

with the team to develop GenAI proof-of-concepts (POCs) for clients using technologies like Retrieval-Augmented Generation (RAG) and intelligent agents. Scale existing POCs to production-ready solutions for customer use. Design and develop FullStack applications for both GenAI and non-GenAI projects. ...

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 ...

Lineage, Master Data Management, and enterprise data catalogues. Strong knowledge of Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), LLM integration, Vector Databases, and AI governance frameworks. Significant experience leading technical pre-sales engagements and developing complex solution architectures. Demonstrable experience responding to large ...

cross-functional organizations.Deep knowledge of modern AI technologies including large language models (LLMs), agentic frameworks, retrieval-augmented generation (RAG), vector databases, and automation platforms — with the credibility to evaluate vendor claims and guide architectural decisions.Experience owning AI governance: building acceptable use policies, risk tiering ...

experience of this would be really useful. Building agentic AI solutions, LLM-powered applications and retrieval-augmented generation (RAG) architectures. Experience with Vertex AI Agent Builder, Agentspace, LangGraph or multi-agent frameworks. Knowledge of responsible AI, model governance and risk management practices within regulated ...

business processes.Act as a Salesforce and AI subject matter expert within the Digital Customer Experience (DCX) practice, helping shape our next-generation consulting capabilities and AI delivery methodologies.Design and develop scalable Salesforce solutions using a combination of declarative and programmatic technologies including Apex, Lightning Web Components … Salesforce data.A working understanding of how large language models behave in practice: prompt engineering, retrieval-augmented generation (RAG), grounding, and how to reduce hallucination.Experience testing and evaluating AI features, for example building eval sets, measuring accuracy, and monitoring quality, cost and latency once live.Knowledge ...

Build and integrate AI-powered features into web applications and enterprise tools. Build and optimize Retrieval-Augmented Generation (RAG) solutions to power chatbot interactions Work both independently and paired with other team members to ensure efficient delivery of prioritised features. Take part … Experience using modern AI-assisted and agentic development workflows in day-to-day engineering usingAI/ML APIs and SDKs Hands-on experience developing RAG solutions or working with LLMs for chatbots is preferred In-depth understanding of CI/CD and the tools used to implement them, such ...