101 to 125 of 208 Retrieval-Augmented Generation Jobs in England

optimized for complex financial workflows Event-driven distributed systems handling sensitive data at enterprise scale The Tech Stack AI/ML : Multi-agent frameworks, fine-tuning, reinforcement learning, advanced RAG Platform : AWS serverless, event-driven architecture, microservices Languages : Python, with modern ML libraries (PyTorch, TensorFlow) What They're Looking For 5+ years developing AI/ML systems beyond basic integration More ❯

to leverage these capabilities in novel, real world use cases. Experience delivering Large Language Model projects with customers, including LLM API integration, current knowledge of foundation models, prompt engineering, RAG, fine tuning, and managing AI projects. You either come from an Engineering background, or your desire to ship working solutions has allowed you to build out a range of technical More ❯

not limited to) Python, Go, TypeScript, React, Kubernetes, Mongo, and Generative AI features requiring adaptability and a willingness to learn. Responsibilities: Lead applied GenAI research, focusing on prompt engineering, RAG, and agentic workflows Architect and deliver end-to-end LLM solutions - from experimentation to production Design evaluation frameworks to benchmark LLM performance, safety, and behaviour Build integration layers connecting LLMs More ❯

learning, and contribute to a culture of innovation. AI & Cloud Expertise Familiarity with LLM evaluation techniques, output scoring, and validation frameworks. Understanding of key concepts such as prompt engineering, RAG, model orchestration, and hallucination detection. Experience in testing for accuracy, relevance, and consistency of AI model predictions/generations Defining Performance Metrics for AI services and testing for the same More ❯

doing Design and maintain pipelines that support LLM-based features - including metadata processing, semantic enrichment, and structured context retrieval. Design infrastructure for scalable and performant RAG systems (retrieval-augmented generation), including support for Graph RAG where adopted. Experience in processing large volumes and varieties of structured text data. Experience with legal documents would be … advanced features, not just move bytes around. You've worked with vector stores and embedding pipelines. You are excited by newer patterns like hybrid and graph-based retrieval (Graph RAG). You're comfortable owning your systems in production and instrumenting them for observability. You value collaboration and can flex across infrastructure, science, and product conversations. Qualifications 5+ … services; experience with Amazon Bedrock or Claude integration is a plus. Experience with vector databases and embedding pipelines. Familiarity with or interest in graph-based data models and Graph RAG architectures is a strong plus. Working knowledge of Java and TypeScript environments, especially for integration and debugging. Experience using Jira to coordinate delivery. Working for Opus 2 Opus 2 is More ❯

OpenAI, Anthropic, etc.) and orchestration frameworks like LangChain, LlamaIndex, or have built custom agent frameworks from scratch. You understand intelligent information retrieval. You have experience with RAG (Retrieval-Augmented Generation) systems, vector databases, and embedding models for knowledge extraction. You can architect complex workflows. You have experience with workflow orchestration tools (Airflow, Prefect, Temporal More ❯

SINDy) Working knowledge of cell biology. Experience with Python, C, R or related scientific computing languages. Preferred Qualifications - Experience working with causal representation learning Experience with RAG (retrieval-augmented generation) and GraphRAG a big plus Experience with building and deploying software on GitHub, PyPI, Anaconda Cloud, and Docker Hub, as well as use of More ❯

work on fine-tuning, integrating, and scaling LLMs for real-world applications. Key Skills: Strong Python engineering background Experience with LLMs (e.g. Hugging Face, OpenAI, LangChain) Model fine-tuning, RAG pipelines, vector databases (e.g. FAISS, Pinecone) Cloud (AWS/GCP), CI/CD, Docker Bonus: Knowledge of model optimization, quantization, or open-source contributions. 📩 If interested send your CV to More ❯

work on fine-tuning, integrating, and scaling LLMs for real-world applications. Key Skills: Strong Python engineering background Experience with LLMs (e.g. Hugging Face, OpenAI, LangChain) Model fine-tuning, RAG pipelines, vector databases (e.g. FAISS, Pinecone) Cloud (AWS/GCP), CI/CD, Docker Bonus: Knowledge of model optimization, quantization, or open-source contributions. 📩 If interested send your CV to More ❯

work on fine-tuning, integrating, and scaling LLMs for real-world applications. Key Skills: Strong Python engineering background Experience with LLMs (e.g. Hugging Face, OpenAI, LangChain) Model fine-tuning, RAG pipelines, vector databases (e.g. FAISS, Pinecone) Cloud (AWS/GCP), CI/CD, Docker Bonus: Knowledge of model optimization, quantization, or open-source contributions. 📩 If interested send your CV to More ❯

work on fine-tuning, integrating, and scaling LLMs for real-world applications. Key Skills: Strong Python engineering background Experience with LLMs (e.g. Hugging Face, OpenAI, LangChain) Model fine-tuning, RAG pipelines, vector databases (e.g. FAISS, Pinecone) Cloud (AWS/GCP), CI/CD, Docker Bonus: Knowledge of model optimization, quantization, or open-source contributions. 📩 If interested send your CV to More ❯

work on fine-tuning, integrating, and scaling LLMs for real-world applications. Key Skills: Strong Python engineering background Experience with LLMs (e.g. Hugging Face, OpenAI, LangChain) Model fine-tuning, RAG pipelines, vector databases (e.g. FAISS, Pinecone) Cloud (AWS/GCP), CI/CD, Docker Bonus: Knowledge of model optimization, quantization, or open-source contributions. 📩 If interested send your CV to More ❯

work on fine-tuning, integrating, and scaling LLMs for real-world applications. Key Skills: Strong Python engineering background Experience with LLMs (e.g. Hugging Face, OpenAI, LangChain) Model fine-tuning, RAG pipelines, vector databases (e.g. FAISS, Pinecone) Cloud (AWS/GCP), CI/CD, Docker Bonus: Knowledge of model optimization, quantization, or open-source contributions. 📩 If interested send your CV to More ❯

work on fine-tuning, integrating, and scaling LLMs for real-world applications. Key Skills: Strong Python engineering background Experience with LLMs (e.g. Hugging Face, OpenAI, LangChain) Model fine-tuning, RAG pipelines, vector databases (e.g. FAISS, Pinecone) Cloud (AWS/GCP), CI/CD, Docker Bonus: Knowledge of model optimization, quantization, or open-source contributions. 📩 If interested send your CV to More ❯

work on fine-tuning, integrating, and scaling LLMs for real-world applications. Key Skills: Strong Python engineering background Experience with LLMs (e.g. Hugging Face, OpenAI, LangChain) Model fine-tuning, RAG pipelines, vector databases (e.g. FAISS, Pinecone) Cloud (AWS/GCP), CI/CD, Docker Bonus: Knowledge of model optimization, quantization, or open-source contributions. 📩 If interested send your CV to More ❯

work on fine-tuning, integrating, and scaling LLMs for real-world applications. Key Skills: Strong Python engineering background Experience with LLMs (e.g. Hugging Face, OpenAI, LangChain) Model fine-tuning, RAG pipelines, vector databases (e.g. FAISS, Pinecone) Cloud (AWS/GCP), CI/CD, Docker Bonus: Knowledge of model optimization, quantization, or open-source contributions. 📩 If interested send your CV to More ❯

be necessary for meetings, but these will be fully funded. As a GenAI/Python Engineer , you’ll help design, build, and scale AI-powered applications using tools like RAG, intelligent agents, and LLMs. This hands-on, client-facing role blends technical depth with consulting impact. You will: Develop and scale GenAI solutions from POCs to production. Lead development across More ❯

be necessary for meetings, but these will be fully funded. As a GenAI/Python Engineer , you’ll help design, build, and scale AI-powered applications using tools like RAG, intelligent agents, and LLMs. This hands-on, client-facing role blends technical depth with consulting impact. You will: Develop and scale GenAI solutions from POCs to production. Lead development across More ❯

What We’re Looking For Strong experience in software engineering (preferably 5+ years) Proficiency with Python, data processing, microservices, and distributed systems Experience working with Large Language Models (LLMs), RAG pipelines, or similar AI tooling Comfortable owning technical delivery and leading small teams Strong communication skills - able to engage with both technical and non-technical stakeholders Ability to manage multiple More ❯

What We’re Looking For Strong experience in software engineering (preferably 5+ years) Proficiency with Python, data processing, microservices, and distributed systems Experience working with Large Language Models (LLMs), RAG pipelines, or similar AI tooling Comfortable owning technical delivery and leading small teams Strong communication skills - able to engage with both technical and non-technical stakeholders Ability to manage multiple More ❯

high 2:1, preferably in a technical subject Proficiency in Python and its ecosystem Active engagement with the AI space and proactive exploration of new AI technologies (Agents, MCP, RAG, Chain-of-Continuous-Thought, etc. More ❯

in the fastest-moving fields of current AI research, in particular in how to integrate a broad range of structured and unstructured multimodal information into AI systems (e.g. with RAG techniques), and get to immediately apply your results in highly visible Amazon products. If you are deeply familiar with LLMs, natural language processing and machine learning, this may be the More ❯

LLMs (Codex, ChatGPT, Claude, etc.) into the dev lifecycle Apply AI to requirements, design, coding, QA, CI/CD, and monitoring Optimize internal AI toolchains with platform team (OpenWebUI, RAG, etc.) Drive Salesforce Revenue Cloud automation: pricing, CPQ, billing Automate contracts, provisioning, onboarding, and payment flows Define and own subscription models, trials, usage-based billing, and provisioning logic Align engineering More ❯

LLMs (Codex, ChatGPT, Claude, etc.) into the dev lifecycle Apply AI to requirements, design, coding, QA, CI/CD, and monitoring Optimize internal AI toolchains with platform team (OpenWebUI, RAG, etc.) Drive Salesforce Revenue Cloud automation: pricing, CPQ, billing Automate contracts, provisioning, onboarding, and payment flows Define and own subscription models, trials, usage-based billing, and provisioning logic Align engineering More ❯

LLMs (Codex, ChatGPT, Claude, etc.) into the dev lifecycle Apply AI to requirements, design, coding, QA, CI/CD, and monitoring Optimize internal AI toolchains with platform team (OpenWebUI, RAG, etc.) Drive Salesforce Revenue Cloud automation: pricing, CPQ, billing Automate contracts, provisioning, onboarding, and payment flows Define and own subscription models, trials, usage-based billing, and provisioning logic Align engineering More ❯