201 to 225 of 244 Retrieval-Augmented Generation Jobs in the UK

a founder or founding engineer - you know what it means to balance craft, ownership, and speed Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering Prior experience with React, TypeScript, and/or Go Previous roles where you interfaced with customers or led technical projects with external stakeholders Our values Trust More ❯

as well as TR product and technology leaders to define and deliver on the Corporates Tax & Trade AI vision. Experience designing and implementing solutions with large language models, including RAG frameworks and agentic frameworks Outstanding communication and data-driven decision-making Preferred qualifications: 8+ years of management experience - coaching & developing high-performing teams Experience innovating state-of-the-art research More ❯

Conversational AI technologies, like natural language understanding/generation, dialog systems, machine translation, and information retrieval. Experience of developing information retrieval systems, Fine Tuning for RAG & Direct Preference optimisation Experience of ML Ops environments & platforms The more experience you have of adapting LLM's for different domains the better (although this isn't a must have More ❯

AI Research Engineer to help pioneer next-generation language model systems at the frontier of applied AI. In this role, you’ll help build foundational agent and RAG infrastructure, shape internal research initiatives, and accelerate the delivery of LLM-powered features to end users. You’ll collaborate cross-functionally with engineering and product teams to experiment, evaluate, and … System Development : Research, prototype, and build systems powered by large language models, focusing on reliability, efficiency, and relevance. Agent & RAG Architectures : Design and refine agentic workflows and retrieval-augmented generation pipelines that improve performance, accuracy, and cost-efficiency. Evaluation & Alignment : Develop metrics and tools to measure model performance, groundedness, and behaviour; explore fine-tuning More ❯

AI Research Engineer to help pioneer next-generation language model systems at the frontier of applied AI. In this role, you’ll help build foundational agent and RAG infrastructure, shape internal research initiatives, and accelerate the delivery of LLM-powered features to end users. You’ll collaborate cross-functionally with engineering and product teams to experiment, evaluate, and … System Development : Research, prototype, and build systems powered by large language models, focusing on reliability, efficiency, and relevance. Agent & RAG Architectures : Design and refine agentic workflows and retrieval-augmented generation pipelines that improve performance, accuracy, and cost-efficiency. Evaluation & Alignment : Develop metrics and tools to measure model performance, groundedness, and behaviour; explore fine-tuning More ❯

What "Great" Looks Like Prompt & RAG Engineering Design, tune, and A/B-test prompt chains that improve instruction-following accuracy, session-completion detection, and overall Buddy engagement. Implement RAG pipelines to support both support bots and in-product answers. Multi-language Scale-out Modularize Buddy prompt chains so each language pair uses a single, well-structured template with language … taking ownership of high-impact deliverables that influence KPIs. Must-Have Prompt engineering best practices Proactiveness and strong ownership mindset Retrieval-Augmented Generation (RAG) techniques Nice-to-Have Foundations of recommender systems Experience with A/B testing at scale Proficiency in Python (LLM tooling) and Kotlin Knowledge of ML-ops tools (Airflow, Feature More ❯

London, the postdoc will work on shaping the future of AI-driven shopping experiences at Amazon. In particular, the project focuses on conversational search in shopping, developing next-generation conversational search systems in the shopping domain that seamlessly bridge natural shopping dialogues with precise product retrieval and recommendation. Key challenges include developing new methods for grounding … techniques in a variety of areas and innovate on behalf of shoppers, advertisers, and customers. In this role you will: Lead research projects in conversational search and retrieval-augmented systems Develop novel architectures combining dialogue management with product search Design and implement evaluation frameworks for agentic conversational shopping systems Publish research findings in top-tier conferences … Machine Learning, Information Retrieval or related field Strong publication record in NLP, Information Retrieval, or Conversational AI Experience with large language models and retrieval-augmented generation Research background in conversational systems or dialogue management Experience with modern deep learning frameworks (PyTorch, TensorFlow) Excellent written and verbal communication skills PREFERRED QUALIFICATIONS More ❯

feature work* •⁠ ⁠Design and ship REST or GraphQL endpoints. •⁠ ⁠Build multi-tenant data models and role-based workflows. •⁠ ⁠Trigger emails and webhooks for status changes. *AI/Retrieval-Augmented Generation* •⁠ ⁠Wire existing prompts to an LLM API (OpenAI-compatible today, private model later). •⁠ ⁠Store embeddings in a vector store and perform RAG look More ❯

feature work* •⁠ ⁠Design and ship REST or GraphQL endpoints. •⁠ ⁠Build multi-tenant data models and role-based workflows. •⁠ ⁠Trigger emails and webhooks for status changes. *AI/Retrieval-Augmented Generation* •⁠ ⁠Wire existing prompts to an LLM API (OpenAI-compatible today, private model later). •⁠ ⁠Store embeddings in a vector store and perform RAG look More ❯

Already live with its first product and early revenue projected (high six-figure ARR this year), the company is now developing a second, more ambitious system that uses LLMs, RAG, and multi-source data ingestion to solve real problems in a complex, high-value industry. This is a rare opportunity to join early, build real AI systems, and take ownership … deployment experience Strong exposure to MLops/LLMops, ideally in real-world AI product builds Experience with unstructured data, search/re-ranking, or retrieval systems (e.g., RAG) A “builder” mindset, fast, hands-on, pragmatic, collaborative Excited by early-stage start-up life More ❯

Already live with its first product and early revenue projected (high six-figure ARR this year), the company is now developing a second, more ambitious system that uses LLMs, RAG, and multi-source data ingestion to solve real problems in a complex, high-value industry. This is a rare opportunity to join early, build real AI systems, and take ownership … deployment experience Strong exposure to MLops/LLMops, ideally in real-world AI product builds Experience with unstructured data, search/re-ranking, or retrieval systems (e.g., RAG) A “builder” mindset, fast, hands-on, pragmatic, collaborative Excited by early-stage start-up life More ❯

teams reach high-intent buyers through hyper-personalised, multi-channel campaigns. We’re building an AI-first platform from the ground up, with LLMs powering everything from content generation to strategic recommendations. We’re looking for hands-on AI Fullstack Product Engineers who’s excited to build, ship, and fully own production-grade AI features. You’ll have … ll be responsible for architecting and shipping AI-powered features using tools like PydanticAI, LangGraph, FastAPI, and OpenAI/Anthropic APIs. You’ll build and orchestrate intelligent agents and RAG pipelines, moving quickly to prototype, test, and launch in days, not months. Working closely with product, design, and go-to-market teams, you’ll build features that solve real customer More ❯

teams reach high-intent buyers through hyper-personalised, multi-channel campaigns. We’re building an AI-first platform from the ground up, with LLMs powering everything from content generation to strategic recommendations. We’re looking for hands-on AI Fullstack Product Engineers who’s excited to build, ship, and fully own production-grade AI features. You’ll have … ll be responsible for architecting and shipping AI-powered features using tools like PydanticAI, LangGraph, FastAPI, and OpenAI/Anthropic APIs. You’ll build and orchestrate intelligent agents and RAG pipelines, moving quickly to prototype, test, and launch in days, not months. Working closely with product, design, and go-to-market teams, you’ll build features that solve real customer More ❯

and verifiable in our product, whether that’s code or more unstructured outputs. We have frameworks for evaluation, verification, specialized code and test generation pipelines, agentic behavior, RAG, observability and orchestration tooling, and many more... all widely used across our product, neatly integrated, and informed by real customer and product needs. Each of these are constantly evolving to … necessary. You either have professional experience using LLMs or have enthusiastically experimented in your own time. Industry experience with LLM toolchains and ecosystems (e.g. libraries like Langchain, observability tooling, RAG systems, etc.) is a plus. You have a fundamental understanding of code analysis, compilers, domain-specific languages, or related topics, and are keen to learn in this area. You are More ❯

and verifiable in our product, whether that’s code or more unstructured outputs. We have frameworks for evaluation, verification, specialized code and test generation pipelines, agentic behavior, RAG, observability and orchestration tooling, and many more... all widely used across our product, neatly integrated, and informed by real customer and product needs. Each of these are constantly evolving to … necessary. You either have professional experience using LLMs or have enthusiastically experimented in your own time. Industry experience with LLM toolchains and ecosystems (e.g. libraries like Langchain, observability tooling, RAG systems, etc.) is a plus. You have a fundamental understanding of code analysis, compilers, domain-specific languages, or related topics, and are keen to learn in this area. You are More ❯

serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is responsible for contributing to More ❯

teams to quickly prototype and deliver innovative solutions Building complex agentic systems that utilize LLMs Developing scalable distributed information retrieval systems, such as search engines, knowledge graphs, RAG, indexing, ranking, query understanding, and distributed data processing The expected salary range for this position is: Annual Salary: £250,000-£340,000 GBP Logistics Education requirements: We require at least More ❯

trajectory forecasted for 2025. Our platform is already trusted by nearly half of the top 50 financial institutions globally. 🧠 The Technology At the core of our platform is a RAG-based architecture , purpose-built for finance. It’s designed to replicate the kind of deep reasoning you see in leading models like OpenAI’s o1—capable of parsing nuanced questions … frameworks (Python, React, TypeScript, etc.) and can build production-ready systems end-to-end Are excited by AI-native product design and have experience working with or around LLMs, RAG, or agent-like architectures Love talking to users and solving real business problems—not just coding in a vacuum Bring an entrepreneurial mindset , with an eye toward growing into a More ❯

principles Practical MLOps experience of training and tuning deep learning models and evaluating performance (e.g working with PyTorch to build deep learning pipelines) Experience with large language models including; RAG, prompt engineering, and finetuning techniques as well as model API integration Experience across a range of deployment environments including public cloud and high-performance computing clusters Practical experience creating user More ❯

principles Practical MLOps experience of training and tuning deep learning models and evaluating performance (e.g working with PyTorch to build deep learning pipelines) Experience with large language models including; RAG, prompt engineering, and finetuning techniques as well as model API integration Experience across a range of deployment environments including public cloud and high-performance computing clusters Practical experience creating user More ❯

.NET Unit testing frameworks ( i.e. XUnit , NUnit , MSTest ) Having experience with the following technologies is a plus: Tailwind CSS AI Coding Assistance Embeddings, Azure Open AI/Open AI, RAG, Vector Databases, and Semantic Search Working containers via Docker, K8s, and/or Azure Container Instances Frontend unit testing experience is a plus ( i.e. Jest, Vitest ) Education in Computer Science More ❯

growth startups (Monzo, N26, Personio). Demonstrable ability in building and leading high-calibre engineering teams . Experience leading engineering teams working on Generative AI (Prompt Engineering, Fine Tuning, RAG) Competencies: Understanding Technical Requirements with a Focus on Quality: Translate product requirements into squad plans and capacity, while also having a keen eye for ensuring high coding standards, maintainability, and More ❯

As our GTM Manager - London you will focus on the identification and generation of new business opportunities across UK. You will contribute to BRYTER's growth directly by aligning and reinforcing the value of the BRYTER product suite to the customer's overall business plan and strategic objectives and decision criteria. In this role you will be an … Technology: You'll be at the forefront of tech, working with advanced AI models, including large language models (LLMs) and Retrieval-Augmented Generation (RAG) techniques, gaining hands-on experience with the latest innovations. High-impact role : Your contributions will directly shape BRYTER's growth and success. Collaborative and innovative team : Join a company with More ❯

Technology: You'll be at the forefront of tech, working with advanced AI models, including large language models (LLMs) and Retrieval-Augmented Generation (RAG) techniques, gaining hands-on experience with the latest innovations. High-impact role: Your contributions will directly shape BRYTER's growth and success. Collaborative and innovative team: Join a company with More ❯

platform like Kubeflow. Demonstrated ability to transition models from prototype to production. Experience assessing various AI/ML technologies and models for fit to problem space, including scenarios where RAG is applicable. Incident response experience, and ability to work with large, noisy, and rapidly evolving threat datasets. Strong background in cloud engineering and containerisation (Docker, Kubernetes) with experience deploying AI More ❯