301 to 325 of 953 Retrieval-Augmented Generation Jobs in England

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 ...

capabilities are 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 with ...

custom orchestration frameworks . Integrate leading and self-hosted LLMs with tools, data and external systems using MCP and custom connectors . Implement RAG solutions using vector databases and hybrid retrieval where appropriate. Work across relational, document, key-value and graph databases depending on the problem. Develop prompt ...

associated data science ecosystem (Pandas, NumPy, Scikit-learn).* Machine learning techniques including classification, regression, clustering and anomaly detection.* Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions.* SQL and large-scale data analysis.* Cloud-based data science platforms and MLOps practices.* Data visualisation and storytelling tools.### ...

implementing end-to-end AI/ML solutions from development through to deployment and monitoring * Building scalable Generative AI and Agentic AI solutions, including RAG pipelines and orchestration frameworks * Implementing MLOps frameworks, governance and best practices * Translating business requirements into cloud-native AI and data architectures across Azure ...

cloud‐native delivery patterns What Will Make You Stand Out Experience building, deploying, and evaluating multi‐agent AI solutions, agent orchestration patterns, RAG architectures, and enterprise integrations Knowledge of agent communication protocols and interoperability patterns, such as MCP and A2A Ability to balance innovation with practical delivery considerations, including risk ...

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 machine ...

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 ...

designing or delivering AI, data science, machine learning, advanced analytics, or intelligent automation solutions.2+ years of hands-on or architecture experience with GenAI, LLMs, RAG, AI agents, orchestration frameworks, or enterprise AI platforms. Deep understanding of AI architecture considerations, including data readiness, model selection, security, responsible AI, governance, integration, scalability ...

designing or delivering AI, data science, machine learning, advanced analytics, or intelligent automation solutions.2+ years of hands-on or architecture experience with GenAI, LLMs, RAG, AI agents, orchestration frameworks, or enterprise AI platforms.Deep understanding of AI architecture considerations, including data readiness, model selection, security, responsible AI, governance, integration, scalability, observability ...

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 strict coding standards, code ...

Forward Deployment Engineer, you should have experience with:Good technical experience in AI/ML with experience developing and deploying solutions using LLMs, RAG architectures, and modern AI frameworks and protocols (Strands, FastMCP, LangChain, LlamaIndex, Hugging Face, A2A, MCP).Ability to translate multi-layered business problems into technical solutions with ...

Forward Deployment Engineer, you should have experience with: Good technical experience in AI/ML with experience developing and deploying solutions using LLMs, RAG architectures, and modern AI frameworks and protocols (Strands, FastMCP, LangChain, LlamaIndex, Hugging Face, A2A, MCP).Ability to translate multi-layered business problems into technical solutions with ...

libraries (LangChain, LangGraph or related open-source toolkits strongly preferred. Background in Traditional ML/AI is preferred.Deep understanding of LLMs, prompt engineering, RAG pipelines, vector databases, and generative architectures; related security practices and evaluation procedures; hands-on experience fine-tuning, deploying and evaluating large-scale production systems.Hands-on experience ...

organisations from identifying opportunities through to enterprise adoption and measurable business impact. Strong understanding of Generative AI, Agentic AI, Retrieval Augmented Generation (RAG), intelligent assistants and AI-enabled automation, with awareness of major enterprise AI ecosystems such as OpenAI, Google, Anthropic and Microsoft. Experience … Strategy Director, Enterprise AI Consultant, AI Consulting Lead, Data & AI Strategy Consultant, Generative AI, GenAI, Agentic AI, AI Agents, RAG, Retrieval Augmented Generation, Decision Intelligence, Intelligent Automation, AI Operating Models, AI Architecture, Data Platforms, Semantic Layers, Data Products, Responsible AI, AI Governance, Cloud Data ...

organisations from identifying opportunities through to enterprise adoption and measurable business impact. Strong understanding of Generative AI, Agentic AI, Retrieval Augmented Generation (RAG), intelligent assistants and AI-enabled automation, with awareness of major enterprise AI ecosystems such as OpenAI, Google, Anthropic and Microsoft. Experience … Strategy Director, Enterprise AI Consultant, AI Consulting Lead, Data & AI Strategy Consultant, Generative AI, GenAI, Agentic AI, AI Agents, RAG, Retrieval Augmented Generation, Decision Intelligence, Intelligent Automation, AI Operating Models, AI Architecture, Data Platforms, Semantic Layers, Data Products, Responsible AI, AI Governance, Cloud Data ...

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 … third-party services via MCP and related protocols, and define the patterns other engineers build againstImplement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integrationBuild and deliver compelling proofs of concept, live demonstrations ...

founders with a track record of successful exits. With teams across the US, UK, and India, we’re building the next generation of enterprise AI and we’re looking for exceptional people to help us scale. Who You Are You're a customer‐focused AI consultant and software … designing and delivering enterprise software, cloud, or AI solutions for customers. Strong understanding of Large Language Models, Generative AI, Retrieval‐Augmented Generation (RAG), AI agents, and enterprise AI architectures. Experience with cloud platforms including AWS, Azure, or Google Cloud Platform. Understanding of APIs, microservices ...

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 ...

advanced degree preferred. Agentic AI/LLMs: LLM orchestration, prompt engineering, context‐window management and production guardrails; MCP, tool‐augmented agents and RAG at enterprise scale. Enterprise integration: Integrating AI into enterprise systems via APIs and data pipelines, with strong security, data governance and residency practices. Cloud ...

equivalent; advanced degree preferred.Agentic AI/LLMs: LLM orchestration, prompt engineering, context-window management and production guardrails; MCP, tool-augmented agents and RAG at enterprise scale.Enterprise integration: Integrating AI into enterprise systems via APIs and data pipelines, with strong security, data governance and residency practices.Cloud: AWS, Azure ...

advanced degree preferred. Agentic AI/LLMs: LLM orchestration, prompt engineering, context-window management and production guardrails; MCP, tool-augmented agents and RAG at enterprise scale. Enterprise integration: Integrating AI into enterprise systems via APIs and data pipelines, with strong security, data governance and residency practices. Cloud ...

SkillsPython and associated data science ecosystem (Pandas, NumPy, Scikit-learn).Machine learning techniques including classification, regression, clustering and anomaly detection.Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions.SQL and large-scale data analysis.Cloud-based data science platforms and MLOps practices.Data visualisation and storytelling tools.Desirable SkillsExperience within financial ...

associated data science ecosystem (Pandas, NumPy, Scikit-learn).Machine learning techniques including classification, regression, clustering and anomaly detection. Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions. SQL and large-scale data analysis. Cloud-based data science platforms and MLOps practices. Data visualisation and storytelling tools. Desirable ...

/inference optimization, MLOps lifecycle management, and integration with cloud‐native services. GenAI Leadership: Serve as a practitioner for enterprise GenAI solutions, specializing in RAG architectures, agentic systems (including tool‐calling, multi‐agent orchestration, and guardrails), AI observability, and natural language querying of structured data. Provide advanced technical support ...