201 to 225 of 842 Retrieval-Augmented Generation Jobs in the UK

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 ...

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 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 ...

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 ...

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 ...

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 ...

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 ...

when not to Hands-on experience building, evaluating, and deploying machine learning models into production Practical experience with Large Language Models, including prompt engineering, RAG, fine-tuning, and agentic frameworks Practical experience with CI/CD, containerisation, and cloud-native deployment patterns Demonstrated experience delivering system design, application development, testing ...

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 ...

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 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 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 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 ...

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 ...

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 ...

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 ...

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 … 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 ...

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 ...