76 to 100 of 172 Retrieval-Augmented Generation Jobs in the UK

levels. What you'll bring: Proven experience (3 years) in AI solution engineering, with a focus on large language models, prompt engineering, and RAG implementations. Strong skills in data analytics, MLOps practices, and API development. Knowledge of governance frameworks for AI/ML models. Python expertise for automation. Experience working ...

technologies Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps, LLMOps and model lifecycle management principles Experience ...

technologies Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps, LLMOps and model lifecycle management principles Experience ...

technologies Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps, LLMOps and model lifecycle management principles Experience ...

datastores AI & Automation Hands-on experience integrating LLMs, AI APIs (OpenAI, Azure OpenAI, etc.), or ML models into production applications Familiarity with agentic frameworks, RAG pipelines, or AI-assisted workflow automation Ability to assess where AI genuinely adds value and communicate that clearly to non-technical stakeholders Mindset & Adaptability Proven ...

Required Experience Strong programming skills, particularly in Python Experience with machine learning and AI, including LLMs or related technologies Knowledge of areas such as RAG architectures, agent-based AI, computer vision, or audio processing Experience working with cloud platforms (AWS or Azure preferred) Familiarity with Docker, Linux/Unix environments ...

technical teams or senior specialists in high stakes modelling environments/li , li Deep understanding of AI/ML systems including LLMs, agentic architectures, RAG pipelines, credit or pricing models, or risk modelling techniques/li , li Hands-on experience developing or validating models, performing statistical testing, and analysing model ...

Proven experience leading AI, machine learning, or intelligent automation initiatives in a mid-to-large organisation Strong hands-on knowledge of generative AI (LLMs, RAG architectures) and/or agentic AI frameworks Experience building or scaling AI/data science teams Track record of delivering AI solutions into production environments ...

Proven experience leading AI, machine learning, or intelligent automation initiatives in a mid-to-large organisation Strong hands-on knowledge of generative AI (LLMs, RAG architectures) and/or agentic AI frameworks Experience building or scaling AI/data science teams Track record of delivering AI solutions into production environments ...

skills, ideally including FastAPI. Strong AWS experience, including services such as Bedrock, Lambda, ECS/EKS, API Gateway and S3. Experience with LangChain, LangGraph, RAG, vector databases and multi-agent systems. Experience building APIs, platforms, tools and AI-enabled products. Familiarity with evaluation and observability tools such as Arize, Promptfoo ...

Familiarity with AI-assisted development tools such as GitHub Copilot, Claude, and Cursor. Azure AI Engineer certification or equivalent practical experience. Understanding of MCP, RAG architectures, or vector databases. Benefits Industry-leading training and development opportunities. Competitive salary with progression potential. 23-days holiday allowance, increasing with length of service ...

models (DAX and Power Query) Exposure to ML/AI concepts (e.g. scikit-learn, TensorFlow) or an interest in preparing data for LLMs, RAG architectures or predictive models Experience with Docker and/or Terraform (desirable) What You Will Learn & What Liquidline Can Offer You Being a part of Liquidline ...

EventBridge, SQS, Step Functions Databases: DynamoDB, PostgreSQL, Aurora, MongoDB Frontend: React, TypeScript, MUI DevOps: AWS CDK, Terraform, Docker, GitLab CI, CodePipeline AI: Amazon Bedrock, RAG, LLM integrations Skills Required Commercial software engineering experience Strong AWS cloud/serverless experience Strong backend development skills in TypeScript, Python, or Go CI/ ...

premises, cloud, and hybrid AI solutions. GenAI Leadership: Deploy and customize a variety of generative models, leveraging Azure OpenAI, Vector Databases, and RAG patterns. Technical Governance: Managed and governed technical teams to ensure best practices in AI data engineering. Stakeholder Management: Act as the primary technical point of contact, gaining ...

premises, cloud, and hybrid AI solutions. GenAI Leadership: Deploy and customize a variety of generative models, leveraging Azure OpenAI, Vector Databases, and RAG patterns. Technical Governance: Managed and governed technical teams to ensure best practices in AI data engineering. Stakeholder Management: Act as the primary technical point of contact, gaining ...

prioritise AI opportunities across the organisation Required ExperienceEssential Deep expertise in Python and relevant AI/ML frameworks and SDKs Proven experience building RAG pipelines that operate effectively in production environments Hands-on experience with model packaging, deployment, and production AI workflows Strong understanding of enterprise infrastructure concepts including VNets ...

agentic AI architectures, with experience integrating AI securely and at scale Practical experience in enterprise AI governance, prompt engineering, and deployment approaches (including RAG, fine-tuning considerations, and risk mitigation) Experience leveraging AI-assisted development tools (e.g. GitHub Copilot, Claude Code) to materially improve engineering productivity and delivery outcomes ...

agentic AI architectures, with experience integrating AI securely and at scale Practical experience in enterprise AI governance, prompt engineering, and deployment approaches (including RAG, fine-tuning considerations, and risk mitigation) Experience leveraging AI-assisted development tools (e.g. GitHub Copilot, Claude Code) to materially improve engineering productivity and delivery outcomes ...

LLaMA, Mistral, Claude). Fine-tune large language models for domain-specific applications. Implement advancedprompt engineeringstrategies. LeverageRetrieval-Augmented Generation (RAG)for enhanced contextual performance. Build intelligent agents using frameworks likeLangChain, LlamaIndex, CrewAI, AutoGen. Applyreinforcement learningtechniques includingQ-learning,policy gradients, andRLlib. Collaborate with cross-functional teams ...

agent-style or multi-step AI workflows Using LLMs (Azure OpenAI/OpenAI) in real applications Implementing prompt engineering in production environments Working with RAG, embeddings, or vector-based search Designing systems with human-in-the-loop controls and governance Understanding of AI reliability, evaluation, and auditability This ...

prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting … collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma ...

prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting … collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma ...

Product Engineer (Full Stack/AI Systems) We are building a new generation of AI-powered products and are looking for a hands-on AI Product Engineer to help design, build, and scale intelligent systems in production. This is not a pure research or infrastructure role. … frontend engineers and product teams collaboratively Strong curiosity and product mindset - asking the right questions, not just writing code Desirable experience RAG (Retrieval-Augmented Generation) systems or agent-based AI workflows Kubernetes or containerised deployment environments Event-driven architectures and scalable system design Experience ...

Ability to work in fast-paced, delivery-focused projects Desirable Skills Experience with Power Platform (Power Automate, Power Apps) Knowledge of RAG (Retrieval-Augmented Generation) architectures Familiarity with enterprise data security and compliance in AI solutions Previous consulting or client-facing delivery experience Working ...

Engineering community. What youll bring: A strong understanding of AI, machine learning and agent-based AI concepts, including Retrieval Augmented Generation (RAG), multi-agent systems and conversational agents. Experience developing AI solutions using programming languages such as Python, or similar languages used ...