276 to 300 of 954 Retrieval-Augmented Generation Jobs in England

Role Join our AI Engineering division in London to specialize in LLM fine-tuning, retrieval-augmented generation (RAG), and hosting private models. You will be responsible for tailoring deep learning models to specialized domain tasks. Key Responsibilities Fine-tune open-source models (Llama, Mistral ...

contribute high-quality production code while guiding technical directionDeep hands-on expertise building enterprise AI applications using large language models, AI agents, retrieval-augmented generation, prompt engineering, orchestration frameworks, evaluation methods, and model optimisation techniquesProven ability to take complex AI solutions from prototype … inference pipelines, and platform capabilities that support real-time and batch AI workloads at enterprise scaleImplement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integrationMake key technical decisions while remaining accountable for practical ...

high-quality production code while guiding technical direction - Deep hands-on expertise building enterprise AI applications using large language models, AI agents, retrieval-augmented generation, prompt engineering, orchestration frameworks, evaluation methods, and model optimisation techniques - Proven ability to take complex AI solutions from prototype … pipelines, and platform capabilities that support real-time and batch AI workloads at enterprise scale - Implement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration - Make key technical decisions while remaining accountable ...

high-quality production code while guiding technical direction - Deep hands-on expertise building enterprise AI applications using large language models, AI agents, retrieval-augmented generation, prompt engineering, orchestration frameworks, evaluation methods, and model optimisation techniques - Proven ability to take complex AI solutions from prototype … pipelines, and platform capabilities that support real-time and batch AI workloads at enterprise scale - Implement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration - Make key technical decisions while remaining accountable ...

technical direction credibly and make sound architecture decisions.• Demonstrated experience with AI/ML technologies, including LLMs, Retrieval Augmented Generation (RAG), agentic workflows, Natural Language Processing (NLP), and predictive analytics, and the discipline to run them reliably in production.• Track record of building … estate.• Across TR: Legal, Data & Analytics, CTO, Product, CIO and wider CDO organisations, and Internal Audit.Technologies You'll Work With• LLMs and agentic frameworks• RAG architectures• AI agents and orchestration (e.g. LangChain/LangGraph)• Python and modern data engineering• Snowflake and governed semantic layers• AWS/GCP cloud services• Vector ...

doesn't make sense, and delivering in short, time-boxed cycles where validated outcomes matter more than perfect solutions. Agentic AI/LLMs: Building RAG pipelines, tool-augmented agents and agentic workflows; familiar with prompt engineering, context management, evaluation and observability. Agent fundamentals: Understands how agents use memory ...

software engineering, AI engineering or machine learning engineering.•Strong Python development skills and experience building production-grade distributed systems.•Hands-on experience with LLMs, RAG, agent frameworks, prompt engineering, tool calling and context engineering.•Experience designing APIs, microservices and cloud-native applications.•Knowledge of vector search, semantic retrieval ...

delivered across the organization. Key Responsibilities: Lead the design and build of end-to-end generative AI applications using LangGraph, including agentic workflows, RAG pipelines, and LLM-integrated services. Define and drive architecture for scalable, secure, reliable, and maintainable AI solutions deployed in production. Develop robust, well-tested backend APIs ...

Agentic AI Multi-agent systems Tool calling Function orchestration Workflow automation Planning and reasoning patterns Human-in-the-loop design Knowledge & Retrieval RAG architectures Vector databases Semantic search Enterprise search Document ingestion Knowledge graphs (advantageous) Integration APIs Event-driven architectures Microsoft ecosystem ServiceNow CRM/ERP integration Identity ...

S3. Strong understanding of MLOps tooling, including MLflow, Weights & Biases, or Data Version Control (DVC). Experience developing LLM or Generative AI applications, including RAG architectures and prompt engineering. Knowledge of LLMOps frameworks such as LangChain, LangGraph, or LangSmith. Experience taking ML models from experimentation into production environments. Strong communication ...

deploy production-grade AI and ML solutions, including GenAI and LLM-enabled systems.Shape AI solution architectures, selecting appropriate patterns (e.g. batch vs streaming, RAG, feature stores, model serving).Lead AI/ML workstreams end-to-end, including planning, delivery governance, and stakeholder management.Mentor and support AI engineers, data scientists ...

concepts from idea to production.Strong knowledge of deep learning, NLP, and LLM architectures and experience in fine-tuning LLMs or training domain-specific models, RAG, embeddings, and vector databases.Familiarity with agentic AI concepts and orchestration frameworks.Experience deploying AI solutions on cloud platforms such as Azure, AWS, or GCP.Strong problem-solving ...

deploy production-grade AI and ML solutions, including GenAI and LLM-enabled systems. Shape AI solution architectures, selecting appropriate patterns (e.g. batch vs streaming, RAG, feature stores, model serving).Lead AI/ML workstreams end-to-end, including planning, delivery governance, and stakeholder management. Mentor and support AI engineers, data ...

Lambda, and S3.Strong understanding of MLOps tooling, including MLflow, Weights & Biases, or Data Version Control (DVC).Experience developing LLM or Generative AI applications, including RAG architectures and prompt engineering.Knowledge of LLMOps frameworks such as LangChain, LangGraph, or LangSmith.Experience taking ML models from experimentation into production environments.Strong communication skills with ...

orchestration, multi-step reasoning, or agent frameworks (e.g. LangGraph, LangChain, CrewAI, AutoGen, or similar).Experience with GenAI/LLM systems in a production context (RAG, prompt orchestration, evaluation, guardrails, cost/latency optimisation).Exposure to MCP (Model Context Protocol) and tool-based/function-calling architectures. Experience deploying and operating ...

data engineering, ML engineering, solution engineering, technical consulting, or related hands-on technical roles.2+ years of experience building or deploying AI, ML, GenAI, LLM, RAG, agentic AI, data science, or automation solutions. Hands-on experience with programming languages and frameworks such as Python, JavaScript/TypeScript, FastAPI, Flask, React, LangChain ...

data engineering, ML engineering, solution engineering, technical consulting, or related hands-on technical roles.2+ years of experience building or deploying AI, ML, GenAI, LLM, RAG, agentic AI, data science, or automation solutions.Hands-on experience with programming languages and frameworks such as Python, JavaScript/TypeScript, FastAPI, Flask, React, LangChain, LlamaIndex ...

experience with Python and modern AI/ML frameworks such as PyTorch and/or TensorFlow.Deep understanding of LLMs, Generative AI, prompt engineering, RAG architectures and vector databases.Experience with frameworks and tooling such as LangChain, LangGraph or similar open-source AI toolkits.Experience fine-tuning, evaluating, deploying and monitoring large-scale ...

across the others: Agentic AI & LLM Engineering: Design and build production-grade agentic systems using major LLM SDKs and agent frameworks; deep knowledge of RAG, MCP servers and prompt engineering at scale. Strong opinions on secure, resilient enterprise deployment of LLM-powered systems; current knowledge of the latest model capabilities ...

across the organisation. Responsibilities Technical Leadership & Engineering Design Agentic Systems: Design and scale robust, secure, and production-ready multi-agent workflows, orchestrations, and advanced RAG architectures, in collaboration with Enterprise Architecture principles. Drive delivery by designing and building agentic solutions, spanning from piloting to full implementation Define Engineering Excellence: Establish ...

across the others: Agentic AI & LLM Engineering: Design and build production-grade agentic systems using major LLM SDKs and agent frameworks; deep knowledge of RAG, MCP servers and prompt engineering at scale. Strong opinions on secure, resilient enterprise deployment of LLM-powered systems; current knowledge of the latest model capabilities ...

platforms that support ingestion, storage, governance, analytics, model deployment, monitoring, and integration with enterprise applications.Understanding of generative AI solution patterns, such as retrieval-augmented generation, enterprise search, intelligent assistants, document processing, content generation, and AI-enabled workflow automation.Awareness of AI governance, responsible … Looker, Vertex AI, Model Garden, Document AI, Gemini, or other Google Cloud data, analytics, API management, AI, or generative AI services.Experience designing retrieval-augmented generation architectures using vector search, embeddings, enterprise data sources, access controls, and secure application integration patterns.Experience with MLOps, including model ...

efficiency, productivity, service improvement or risk reduction.The role will design and deliver pragmatic AI-enabled workflow improvements, including generative AI, agentic workflows, retrieval-augmented generation, process automation, analytics and decision-support solutions where appropriate.The role will act as the engineering bridge between a specific … time, budget, policy and control constraints.Preferred:Enterprise GenAI – Experience implementing generative AI or agentic AI solutions in enterprise environments.Knowledge workflows – Experience with retrieval-augmented generation, vector search, knowledge management, document intelligence or workflow orchestration.Regulated industry – Experience in banking, capital markets, financial services or another ...

development, building scalable, resilient, and production-grade systems Hands-on experience developing AI-powered applications, including large language models (LLMs), AI agents, retrieval-augmented generation, prompt engineering, evaluation frameworks, and model optimization techniques Proven ability to take AI solutions from concept and experimentation through … services that power AI applications, intelligent automation solutions, and AI agents Develop and deploy advanced LLM-powered applications using techniques such as retrieval-augmented generation, prompt engineering, evaluation frameworks, and model optimization Create robust data and inference pipelines that support both real-time ...

production software-engineering skills.Experience developing, integrating and operating enterprise software or AI applications.Practical understanding of LLMs, agentic AI, tool calling and retrieval-augmented generation.Experience building APIs, services and data pipelines, with Docker and cloud or on-premises deployments.Understanding of authentication, networking, access control and enterprise security.Experience ...