51 to 75 of 186 Retrieval-Augmented Generation Jobs in the UK

create high-quality pre-trained datasets, fine-tuned industry-specific Large Language Models(LLMs), and Retrieval-Augmented Generation (RAG) pipelines supported by vector databases. Our innovations can reduce Generative Artificial Intelligence(Gen AI) costs by up to 80% and bring Gen AI solutions ...

foundation in software engineering principles for building scalable, maintainable, and production-ready AI systems. Experience in designing and implementing enterprise-grade AI solutions, including RAG-based solutions with LLMs and vector databases (e.g., Pinecone, Weaviate, FAISS). Proven experience in full stack development and AI/ML system implementation within ...

Implementing MLOps foundations including CI/CD, automated testing, monitoring, drift detection and model versioning Building generative AI features such as RAG pipelines, embeddings, and AI agents Developing clean, testable code and APIs using modern engineering practices Ensuring technical delivery aligns with security, governance, architecture and enterprise standards Evaluating ...

teaching. Required experience: Previously built and deployed multi-agent systems end-to-end Strong hands-on expertise with LangGraph Experience with knowledge graphs, RAG and LLM tool orchestration Proven software engineering fundamentals (Python preferred) Solid MLOps grounding: Kubernetes, CI/CD, Docker, cloud platforms (GCP/AWS/Azure) Comfortable ...

problem-solving and technical storytelling abilities. Commitment to ethical AI deployment. Key Skills Advanced Python and backend languages. Expertise in prompt engineering, fine-tuning, RAG, and agentic design. Familiarity with AI tools (GitHub Copilot, ChatGPT, SonarQube, LangChain, etc.). Understanding of observability, security, and compliance in AI systems. Experience with ...

/Vertex AI , including fine-tuning, vector search, and low-latency inference. Build end-to-end LLM applications , leveraging RAG (Retrieval-Augmented Generation) , agentic workflows, and prompt engineering. Implement robust evaluation frameworks to monitor LLM quality, hallucinations, token usage, and content safety. Develop … Looking For Essential 5+ years' experience in machine learning engineering or applied AI roles. Recent, demonstrable experience with LLMs, Generative AI, and/or RAG-based systems . Strong Python skills using frameworks such as PyTorch, TensorFlow, Hugging Face, or Google GenAI . Experience with vector databases and retrieval ...

Lead the design, implementation, and fine-tuning of LLMs and generative AI solutions (OpenAI, Anthropic Claude, Gemini, open-source models). Build and optimize RAG pipelines , vector databases, and prompt engineering strategies. Develop AI-powered applications integrating LLMs with APIs, agents, and workflows. Deploy and monitor AI models on cloud ...

Doing: Designing, developing, and deploying machine learning and AI models Designing, developing, and deploying LLM applications (e.g. GPT, LLaMA, Claude) integrated with RAG pipelines Implementing end-to-end workflows: from data acquisition, cleaning, and feature engineering to model training, deployment, and monitoring Building scalable pipelines and APIs for AI services ...

related field. 5+ years of experience in AI consulting, solution architecture, or applied machine learning. Strong understanding of generative AI models, prompt engineering, and RAG pipelines. Familiarity with cloud platforms (AWS, Azure etc) and enterprise integration patterns. Excellent communication and stakeholder management skills. Company Overview Element ...

/Vertex AI , including fine-tuning, vector search, and low-latency inference. Build end-to-end LLM applications , leveraging RAG (Retrieval-Augmented Generation) , agentic workflows, and prompt engineering. Implement robust evaluation frameworks to monitor LLM quality, hallucinations, token usage, and content safety. Develop … Looking For Essential 5+ years’ experience in machine learning engineering or applied AI roles. Recent, demonstrable experience with LLMs, Generative AI, and/or RAG-based systems . Strong Python skills using frameworks such as PyTorch, TensorFlow, Hugging Face, or Google GenAI . Experience with vector databases and retrieval ...

Responsibilities Design and implement AI/ML and Generative AI models for predictive analytics and marketing applications. Explore solutions using LLMs, embeddings, and RAG pipelines. Collaborate with data engineers on data quality, feature engineering, and pipeline optimization. Translate business needs into analytical solutions and communicate findings effectively. Requirements Bachelor ...

from experimentation into live systems Experience with MLOps tools (MLflow, Weights & Biases, DVC, or similar) Hands-on exposure to LLM/GenAI applications, including RAG Nice to have: Experience with advanced LLM techniques (e.g. agents, tool use) Familiarity with vector databases and feature stores Experience with Docker, Kubernetes, or Infrastructure ...

fine-tune LLM-based applications (chatbots, summarization, document Q&A, report generation, code assistants, etc.). Apply prompt engineering, RAG (Retrieval-Augmented Generation), and context-aware pipelines to ensure accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores … ethics, security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (Pinecone, Weaviate, FAISS, Chroma) for semantic retrieval use cases. Partner with business stakeholders to identify and shape ...

Engineer – Key Responsibilities Generative AI frameworks and tools such as LangChain, LlamaIndex, Hugging Face, and APIs from OpenAI and Anthropic Building RAG (Retrieval-Augmented Generation) prototypes using vector stores and knowledge graphs Developing and testing agentic architectures enabling AI agents that reason, retrieve … least one language suited to AI systems and data workflows Experienced integrating models with APIs, data sources or production systems Curious about LLMs, RAG pipelines (vector and graph-based), and agent frameworks Familiar with cloud-native platforms (AWS/Azure/GCP) and DevOps/DevSecOps practices Collaborative, curious ...

Experience delivering customer-facing products and supporting the full development lifecycle. Excellent communication, stakeholder engagement, and advisory skills. Desirable Experience with Generative AI, LLMs, RAG, LangChain, or Semantic Kernel. Familiarity with Microsoft Power Platform. Front-end experience with React, Angular, Vue.js, Flutter, or Progressive Web Apps. Exposure to edge computing ...

Practical experience with AWS (and ideally Terraform, GitLab CI). Experience with agentic systems or LLM-powered automation (e.g. tool-augmented LLMs, RAG workflows, agents for complex workflows). If this sounds like you, reach ...

engineering experience Strong experience with modern GenAI/LLM frameworks: LangChain, LangGraph, PyTorch, etc. Comfort working with unstructured data: entity extraction, semantic search, vectorisation, RAG-like patterns Awareness of data engineering: pipelines, legacy data extraction, interfacing with data teams Experience or strong curiosity working with Azure and Azure Databricks ...

production code practices) alongside practical TypeScript experience for bot or workflow integrations. Hands-on experience with LLM or conversational-AI systems, including model APIs, RAG patterns, or agent frameworks. Solid Kubernetes and Docker skills, with at least one real production service shipped in containers. Good command of SQL and data ...

Architect & Engineer AI Systems: You won’t just call an API; you will build robust processing architectures that leverage off-the-shelf LLMs, RAG pipelines, and context engineering to solve hard problems. You will benchmark these systems rigorously to ensure they actually work, not just "feel" smart. Build the Backend ...

models, Anthropic Claude, Azure OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding. Appian BPA Platform - Strong ...

models, Anthropic Claude, Azure OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding. Appian BPA Platform - Strong ...

models, Anthropic Claude, Azure OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding. Appian BPA Platform - Strong ...

models, Anthropic Claude, Azure OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding. Appian BPA Platform - Strong ...

Permanent Required Experience of architecting and solutioning in Gen AI, Agentic AI, classic ML and automation space Experience and good understanding of Prompt engineering, RAG pipelines, Supervised/unsupervised Model tuning, MLOps/LLMOps pipelines, and AI observability Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face ...

tools, and enterprise connectors. Skills: 6-8 years in Software/application engineering, AI engineering, or applied data engineering. Strong experience with LLMs, embeddings, RAG, retrieval stacks, and vector stores. Hands-on experience in multi-agent systems, agent orchestration, or MCP-like tool patterns. Proficiency in Python, including ...