26 to 50 of 111 Retrieval-Augmented Generation Jobs in England

personal and professional development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around More ❯

personal and professional development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects Experience with Retrieval-Augmented Generation (RAG) Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills Benefits: Salary of up to around More ❯

with enterprise partners. No two weeks will look the same. Fine-tune and privately deploy LLMs - with a focus on Retrieval-Augmented Generation (RAG) pipelines Build and scale computer vision systems - from object detection to image segmentation Apply NLP to real-world business problems - summarisation, entity recognition, information extraction, and more Train and deploy More ❯

dependable and consistent results Create and implement intelligent workflow systems, integrating LLMs with enterprise applications, APIs, and automation ecosystems Develop Retrieval-Augmented Generation (RAG) architectures to connect organisational knowledge with LLMs Rapidly prototype and refine AI applications, showcasing tangible business benefits Provide guidance on ethical AI implementation, covering governance frameworks, regulatory compliance, and risk … JavaScript for rapid prototyping and system integration Familiarity with workflow automation solutions (UiPath, Power Automate, Zapier, n8n) and API development Practical knowledge of vector databases and embedding technologies for RAG system implementation Outstanding interpersonal skills - capable of converting business challenges into technical AI strategies Background in agile methodologies or dynamic project environments **Please only apply for this role if you More ❯

dependable and consistent results Create and implement intelligent workflow systems, integrating LLMs with enterprise applications, APIs, and automation ecosystems Develop Retrieval-Augmented Generation (RAG) architectures to connect organisational knowledge with LLMs Rapidly prototype and refine AI applications, showcasing tangible business benefits Provide guidance on ethical AI implementation, covering governance frameworks, regulatory compliance, and risk … JavaScript for rapid prototyping and system integration Familiarity with workflow automation solutions (UiPath, Power Automate, Zapier, n8n) and API development Practical knowledge of vector databases and embedding technologies for RAG system implementation Outstanding interpersonal skills - capable of converting business challenges into technical AI strategies Background in agile methodologies or dynamic project environments **Please only apply for this role if you More ❯

time management skills. Bonus skills • Experience deploying and managing applications with Azure and Docker. • Familiarity with frameworks like LangChain and Retrieval-Augmented Generation (RAG) models for AI-driven applications. • Experience with pandas for data manipulation. What’s on offer • Regular salary reviews recognising performance and contribution. • Generous annual leave: 25 days plus three days More ❯

dimensional modelling to deliver consistent, trusted analytics. Enable advanced AI and ML use cases by building pipelines for vector search, retrieval-augmented generation (RAG), feature engineering, and model deployment. Ensure security and governance through robust access controls, including RBAC, SSO, token policies, and pseudonymisation frameworks. Develop resilient data flows for both batch and streaming More ❯

cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and presentation skills. Ensure the ethical use More ❯

cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and presentation skills. Ensure the ethical use More ❯

cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and presentation skills. Ensure the ethical use More ❯

cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and presentation skills. Ensure the ethical use More ❯

third-party services. Develop front-end interfaces using JavaScript and frameworks such as React. Build and deploy Agentic systems and Retrieval-Augmented Generation (RAG) systems with Large Language Models (LLMs). Participate in privacy automation programs, including workflows for user approvals and reviews. Implement and maintain CI/CD pipelines in Jenkins to streamline More ❯

or instruction tuning models for specific tasks Embedding-based augmentation (using vector search to give LLMs access to external knowledge) Retrieval-Augmented Generation (RAG) or similar techniques You've taken messy, real-world data and turned it into useful, structured outputs You can show how your work had impact - whether that's a model More ❯

Ofcom, Openreach, independent networks and ISPs to uncover problems that directly impact how the UK connects. Advance the use of retrieval-augmented generation (RAG), combining LLMs with vector search, to push the boundaries of how AI can be applied to connectivity challenges. Our stack Backend: PHP (Laravel), Python (for AI/ML workflows) Frontend More ❯

Ofcom, Openreach, independent networks and ISPs to uncover problems that directly impact how the UK connects. Advance the use of retrieval-augmented generation (RAG), combining LLMs with vector search, to push the boundaries of how AI can be applied to connectivity challenges. Our stack Backend: PHP (Laravel), Python (for AI/ML workflows) Frontend More ❯

/Scrum methodologies. Hands-on with Einstein GPT, Prompt Builder/Prompt Studio is desirable. Practical knowledge of prompt engineering, retrieval-augmented generation (RAG) and grounding GenAI on CRM data is desirable. Strong problem-solving and analytical skills. Excellent communication and teamwork abilities are required to present your work internally and give confidence to More ❯

Foundry and Microsoft Copilot Studio. Proficiency in Python and familiarity with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn. Experience with Large Language Models, prompt engineering, and RAG implementations. Strong skills in data analytics, API development, and MLOps practices including CI/CD for ML. Excellent technical documentation and communication skills. Desirable knowledge in Docker, Kubernetes, and understanding More ❯

huggingface and LLM offerings by 3rd party vendors. Knowledge of OO programming and software design, i.e., SOLID principles. Knowledge and working experience of AGILE methodologies. Familiarity with Databricks, and RAG application architecture a plus Experience with latency optimisation and quantisation preferred Additional Information What’s in it for you?: Competitive salary that reflects your skills, experience and potential. Discretionary bonus More ❯

designing and managing databases in Postgres. AI/ML Expertise: Build and deploy Agentic systems, MCP servers/clients, and Retrieval-Augmented Generation (RAG) systems with Large Language Models (LLMs). Extract, transform, and load (ETL) data to build vector databases with embedding models. DevOps and Maintenance: Implement CI/CD pipelines to streamline More ❯

driven by technological advancements and a visionary approach to future challenges in the AI space. Responsibilities: Build and refine AI/ML models, focusing on LLM-based solutions including RAG, fine-tuning, and prompt engineering. Design and implement AI-powered solutions, leveraging Python, SQL/NoSQL, and APIs for seamless integration. Prototype and rigorously test AI applications, focusing on improving More ❯

experience Solid expertise in Node.js Experience integrating LLM APIs and open-source models into production systems Hands-on work implementing Retrieval-Augmented Generation (RAG) pipelines Experience designing and optimizing agentic AI workflows Tremendous opportunity offering plenty of scope for career progression in a friendly, innovative environment where you'll be able to bring ideas More ❯

and managing databases in Postgres. Optional Qualifications: Built LLM applications and familiar with the concepts of MCP servers, Agents, and Retrieval-Augmented Generation (RAG) systems. Experience with extract, transform, and load (ETL) data with using Python libraries (e.g. Pandas). Strong understanding of version control systems and CI/CD pipelines to streamline development More ❯

on cutting-edge projects, applying machine learning, NLP, and generative AI to real-world business problems. Key Responsibilities Build and refine AI/ML models, including LLM-based solutions (RAG, fine-tuning, prompt engineering). Design and implement AI-powered applications, integrating with APIs, SQL/NoSQL databases, and Python-based solutions. Prototype and test AI applications, optimizing performance and More ❯

on cutting-edge projects, applying machine learning, NLP, and generative AI to real-world business problems. Key Responsibilities Build and refine AI/ML models, including LLM-based solutions (RAG, fine-tuning, prompt engineering). Design and implement AI-powered applications, integrating with APIs, SQL/NoSQL databases, and Python-based solutions. Prototype and test AI applications, optimizing performance and More ❯

and agentic applications . Are you ready to apply Make sure you understand all the responsibilities and tasks associated with this role before proceeding. You'll work on LLMs, RAG pipelines, model deployment, and cloud-native solutions that drive real-world impact. What you'll bring: Strong coding skills in Java/TypeScript/Python Experience with LLMs, NLP, and More ❯