151 to 175 of 842 Retrieval-Augmented Generation Jobs in the UK

Responsibilities Architectural Leadership & Integration Design and implement enterprise-grade AI platforms - including semantic search, Retrieval-Augmented Generation (RAG), and broader generative AI/agentic capabilities - integrating cleanly with the department's complex Legacy and multi-cloud environments. Responsible AI Governance Embed … team. Alongside the DDaT competencies, given the scale of this programme, hands-on depth across the modern AI engineering stack is essential, not just RAG in isolation: Semantic search, vector/embedding infrastructure, and retrieval architecture design LLM orchestration and agentic frameworks (eg LangChain/LlamaIndex-style tooling ...

agent frameworks (Pydantic, LangChain, custom orchestration). Data pipelines, ETL, embeddings, or vector search Retrieval-augmented generation (RAG) or model-backed workflows High-performance APIs and distributed services Strong understanding of modern cloud environments (AWS preferred). Solid foundation in computer science, distributed systems ...

wider team to develop GenAI proof-of-concepts (POCs) for clients using technologies like Retrieval-Augmented Generation (RAG) and intelligent agents. Scale existing POCs to production-ready solutions for customer use. Design and develop FullStack applications for both GenAI and non-GenAI projects. Support ...

similar customer‐facing role. Experience building AI applications using modern LLM, agentic AI and retrieval-augmented generation (RAG) frameworks. Bachelor's degree or equivalent commercial experience. Cloud platform certifications (Azure, AWS or Google Cloud). Architecture certifications such as TOGAF or equivalent. Experience working ...

/functions callable by AI agents (tool schemas, function calling, structured outputs). Experience with retrieval-augmented generation (RAG) : vector databases (e.g., Pinecone, Weaviate, pgvector), embeddings, and chunking strategies. Working knowledge of prompt engineering and evaluation techniques for agent reliability, safety, and cost control. ...

agentic architectures. Good understanding of modern AI concepts and practices, including: Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Prompt Engineering AI Guardrails AI Evaluation Frameworks Experience with AI frameworks such as Agent Development Kit (ADK), LangChain, LangGraph, CrewAI, or similar. Experience working with ...

transfer learning, text and token classification. Working knowledge of large language models, including prompting and retrieval-augmented generation (RAG).Experience or coursework in Deep Learning frameworks like PyTorch or TensorFlow. Strong problem-solving skills and a curiosity for learning new technologies. Good verbal ...

agentic AI systems using frameworks like LangGraph, Semantic Kernel, AutoGen, or CrewAI. Deep knowledge of Retrieval-Augmented Generation (RAG), Vector databases, prompt engineering best practices, and model selection trade-offs. Strong understanding of AI security risks (prompt injection, data leakage) and data privacy/ ...

both customers and organisations. Modern AI architecture expertise. Deep understanding of machine learning, LLMs, retrieval-augmented generation (RAG), agentic systems and the architectural patterns used to deploy AI solutions at enterprise scale. Engineering and cloud foundations. Strong understanding of software engineering, data architecture ...

both customers and organisations. Modern AI architecture expertise. Deep understanding of machine learning, LLMs, retrieval-augmented generation (RAG), agentic systems and the architectural patterns used to deploy AI solutions at enterprise scale. Engineering and cloud foundations. Strong understanding of software engineering, data architecture ...

will combine deep software engineering experience, excellent judgment and a demonstrable interest in AI to help shape the way we build our next generation of products. Initially working in a small, focused team, you will help lead and progress the development of our foundational AI-native/… principles (REST, SPA...). Microservice architecture, AWS and DevOps. Building LLM-powered features: tool-calling, retrieval-augmented generation (RAG), evaluation/eval harnesses and observability (desirable). Familiarity with model-agnostic tooling and routing, e.g. a proxy/gateway layer (desirable). Agile manifesto ...

generative AI solutions for scientific and knowledge-discovery applications. Develop LLM-powered workflows and retrieval-augmented generation (RAG) systems for search, summarization, question answering, and evidence-grounded insight generation. Build intelligent retrieval, ranking, recommendation, and decision-support capabilities using modern orchestration frameworks … skills and solid machine learning fundamentals. Experience working with large-scale text or content-rich datasets and modern AI/ML frameworks. Experience with RAG, semantic, vector, or hybrid search, along with experimentation and evaluation approaches that measure user impact. Familiarity with cloud platforms and modern software engineering practices. Strong ...

enterprise production environments. Design scalable enterprise AI architectures utilizing Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), AI Agents, Model Context Protocol (MCP), model fine-tuning, inference optimization, vector databases, API integration, AI workflow orchestration, and cloud-native AI services. Collaborate closely … platforms, cloud computing, software engineering, MLOps, solution architecture, or customer-facing technical consulting. Hands-on experience with modern AI technologies including LLMs, Prompt Engineering, RAG, AI Agents, MCP, model fine-tuning, inference optimization, vector databases, AI orchestration frameworks, API integration, and cloud-native AI architectures. Experience developing or deploying enterprise ...

reference architectures, POV frameworks, or architectural playbooks — at scale.Fluency across the modern data and AI stack: cloud data platforms (Snowflake, Databricks, BigQuery), agentic frameworks, RAG, vector databases, LLM orchestration, data governance, and enterprise integration patterns.Experience with prompt engineering, agent lifecycle management, and hands-on prototype development.Hands-on proficiency in programming … Redshift.AI & Agentic Architecture Foundational ML concepts, data preparation, Python, applied AI, Generative AI, prompt engineering, retrieval-augmented generation (RAG), vector stores, and agentic architectures. Hands-on familiarity with platforms like Databricks, Snowflake, SageMaker, or Vertex. Agent lifecycle management, observability, and governance frameworks.Agentforce & Salesforce Platform ...

AWS. Translate business problems into secure, scalable, production-grade AI systems using Amazon Bedrock, retrieval-augmented generation (RAG), agentic workflows, and cloud-native AWS services. Drive architecture standards, model orchestration, governance, observability, and operational excellence across the GenAI lifecycle while collaborating with engineering, security … CloudWatch* Knowledge of scalable, secure, event-driven, and distributed system architectures* Experience integrating structured and unstructured enterprise data sources* Experience with RAG, fine-tuning, model evaluation, data privacy, ethical AI, and cross-functional stakeholder management is expected* Strong understanding of enterprise security architecture, IAM, encryption, and secure AI deployment practices ...

generative AI engineering fundamentals, including: o Prompt engineering and context design. o Context engineering, retrieval-augmented generation (RAG), embeddings and vector search. o Agent orchestration, multi-agent patterns and skills/plugin development. * Experience with cloud-based AI, data, identity and governance services, ideally ...

systems, or conversational AI.Ideally, you also have experience with large language models (LLMs), foundation models, retrieval-augmented generation (RAG), fine-tuning, prompt engineering, or agentic AI architectures. Hands-on experience with AWS AI/ML services such as Amazon Bedrock, Amazon SageMaker, Amazon ...

conversational AI. Ideally, you also have experience with large language models (LLMs), foundation models, retrieval-augmented generation (RAG), fine-tuning, prompt engineering, or agentic AI architectures. Hands-on experience with AWS AI/ML services such as Amazon Bedrock, Amazon SageMaker, Amazon ...

help build the data foundations that power enterprise search, knowledge discovery, AI applications and Retrieval-Augmented Generation (RAG). What you'll be doing Design and build scalable ETL/ELT data pipelines across multiple enterprise data sources Develop data solutions using BigQuery, Google ...

cases for enterprises. Hands-on experience with modern AI/LLM ecosystems, including Retrieval-Augmented Generation (RAG), and familiarity with open-source frameworks such as LangChain, Hugging Face, or PyTorch, along with a solid understanding of how to work with and deploy Large Language ...

enterprise performance, security, and scalability.Agentic AI Implementation: Direct the practical implementation of LLM orchestration, Retrieval-Augmented Generation (RAG), and "Human-in-the-Loop" (HITL) workflows on live customer projects.Standardization & Playbooks: Package learnings, custom connectors, and architectural patterns from active projects into reusable delivery playbooks … platform, including advanced integration patterns, core architecture design, and performance tuning.Agentic AI Architecture: Practical knowledge of multi-agent orchestration, strategic prompt engineering, vector databases (RAG), and establishing token cost and data privacy guardrails.Estimation & Delivery Methodologies: Strong background in Agile/Scrum delivery, defining MVP boundaries, and creating realistic work-breakdown ...

shape how AI powers our product. You'll work across the entire AI feature lifecycle: Architect and implement AI-powered capabilities: code generation, intelligent node creation, and workflow optimizationIntegrate LLM APIs and embedding models for text-to-workflow and natural language code suggestionsDesign and iterate on prompts … fast iteration is second nature to youBonus Points ForExperience fine-tuning LLMs or working with retrieval-augmented generation (RAG) systemsFrontend experience using Vue or ReactTechnical writing or documentationcontributions, especially around developer tools or AIExperience with agent orchestration patterns and state management in multi-step ...

Familiarity with CI/CD pipelines and software development lifecycles Experience with prompt engineering and retrieval-augmented generation (RAG) based architecture Ability to communicate with clarity and credibility across senior engineers, stakeholders, and product partners Preferred Qualifications, Capabilities, and Skills Experience building agentic tools ...

expand agent capabilities, improve decision quality, and support complex business workflows. Design and optimize Retrieval-Augmented Generation (RAG) architectures , including embedding strategies, vector databases, retrieval pipelines, reranking, and context management to maximize response accuracy and relevance. Design and develop APIs, tools ...

Familiarity with CI/CD pipelines and software development lifecycles Experience with prompt engineering and retrieval-augmented generation (RAG) based architecture Ability to communicate with clarity and credibility across senior engineers, stakeholders, and product partners Preferred Qualifications, Capabilities, and Skills Experience building agentic tools ...