576 to 600 of 889 Retrieval-Augmented Generation Jobs in England

build the right thing, not just a technically impressive thing. Technical foundations that match your level: For senior hires, your toolkit includes Python, RAG, API integrations, and agent architecture. For mid-level hires, your learning trajectory and intellectual curiosity matter as much as your current depth. Communication that bridges ...

build the right thing, not just a technically impressive thing. Technical foundations that match your level: For senior hires, your toolkit includes Python, RAG, API integrations, and agent architecture. For mid-level hires, your learning trajectory and intellectual curiosity matter as much as your current depth. Communication that bridges ...

/IEC 27001.Able to understand and communicate emerging AI architecture and governance concepts, including Azure Foundry AI, Azure OpenAI, Microsoft Copilot, Copilot Studio, RAG, MCP and related governance capabilities.An excellent communicator who can explain complex technology clearly to both technical and non-technical audiences.Analytical and confident enough to challenge requirements ...

understanding of enterprise software deployment architectures (cloud, on-premises, hybrid, air-gapped)Working knowledge of or experience with modern AI: LLMs, agentic systems, MCP, RAG, fine-tuning, evals, and responsible AI would be a strong differentiatorComfortable discussing API integrations, model inference, data pipelines, and ML operations with technical stakeholders.Government & Defence ...

decision support, predictive insights, document intelligence, fraud, compliance or customer-service workflows. Familiarity with modern AI and GenAI development approaches, including LLMs, retrieval-augmented generation, prompt design, agent orchestration and model governance. Awareness of AI-enabled SDLC tools and practices such as requirements generation ...

composable/MACH stacks — or equivalent depth in adjacent enterprise platform delivery with a clear trajectory into commerce Proven experience designing LLM-based systems: RAG, tool-calling, multi-agent orchestration, reasoning workflows Experience with vector retrieval architectures and embedding pipelines in production (semantic search, RAG) Experience designing ...

work. Secure AI Application and Cloud‐AI Guardrails: Define secure design patterns for AI‐enabled applications, including LLM‐based features, retrieval‐augmented generation, AI agents, AI APIs, copilots, and automation workflows. Establish cloud security requirements for AI workloads, including identity, secrets, data storage, network … Risk Management Framework, NIST Generative AI Profile, OWASP Top 10 for LLM Applications, or Cloud Security Alliance AI security guidance. (Desirable) Experience with RAG architecture, AI agents, vector databases, AI APIs, prompt engineering, or AI application threat modelling. (Desirable) Experience building security knowledge assistants, prompt libraries, AI‐assisted review workflows ...

responsibilities as the squad's needs evolve.Requirements: Engineering experience: 3+ years in software engineering, with hands-on experience building LLM-powered applications in production (RAG, tool-augmented agents, or agentic workflows).Education: BS in Engineering, Computer Science, or equivalent.Ways of working: Comfortable working autonomously within a defined problem … something 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, tools ...

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 … information to universities. We help innovators turn knowledge into new products. We help health professionals improve patient care and educators train the next generation of doctors and nurses. Connecting quality content and innovative technologies, we make progress go further and happen faster. And by championing inclusion and sustainability ...

that reached real users. Worked with transformer architectures or fine-tuned language models. Designed evaluation frameworks for generative AI systems. Built retrieval, RAG, embedding or semantic-search systems. Worked with large, noisy or multilingual text datasets. Built high-throughput or low-latency data pipelines. Experience operating machine learning … would be valuable, but we do not expect you to know everything: PyTorch, TensorFlow or JAX Hugging Face LLM APIs and open-source models RAG and vector databases Apache Airflow AWS S3 ECS/EKS Redshift Docker Kubernetes GitHub Actions Pulumi or Terraform SQL Model monitoring and observability Distributed processing ...

Inside IR35 Our client, a leading pharmaceutical organisation is looking for an experienced Agentic AI Software Engineer to join a team developing next generation AI platforms, cloud native infrastructure, and intelligent agent based applications that support cutting edge scientific research. Key Skills & Experience Strong Python development experience FastAPI … DevOps practices Production support, monitoring, observability, and incident management Experience with AI/ML frameworks such as PyTorch, TensorFlow, or JAX Exposure to LLMs, RAG, Agentic AI, model serving, or MLOps environments What's on Offer? Work on innovative AI and Agentic AI solutions Hybrid working from London 12-month ...

grade deployment. The role: - Design AI and GenAI architecture strategies and roadmaps - Build scalable AI/ML and Agentic AI platforms - Work across LLMs, RAG, embeddings and semantic search - Support AI deployment, governance and integration patterns - Collaborate with engineering, data, DevOps and business teams - Advise clients on AI platform capability … implementation strategy Tech environment: Python LLMs (prompt engineering, fine-tuning, RAG) LangChain/LangGraph Agent frameworks Vector databases MLOps/LLMOps AWS/Azure/GCP/Databricks Kubernetes & GPU infrastructure What you'll bring: - Experience designing enterprise AI or ML architectures - Strong grasp of cloud and modern data platforms ...

agentic AI systems for enterprise clients, in partnership with leading frontier-model providers. We already support clients from different verticals to have agentic and RAG systems live in production across healthcare, financial services, retail and global logistics. As a Forward Deployed AI Engineer you work embedded in the client … least one of: Anthropic Agent SDK, LangGraph, LlamaIndex, or an equivalent orchestration framework, plus the judgement to know when to use none of them. RAG and retrieval: Chunking strategy, embeddings, hybrid and semantic search, re‐ranking, citation and provenance, natural‐language‐to‐query translation. Data platforms: NoSQL databases ...

user experience.Establish observability and feedback loops that make agent behavior understandable and continuously improvable.Develop the AI Application ArchitectureApply context-engineering techniques such as RAG, MCP and knowledge graphs.Design prompts, tools, memory, workflows and orchestration strategies for production agents.Select and use appropriate orchestration frameworks, such as Google ADK, LangGraph, LangChain, LlamaIndex … below. We care most about strong engineering judgment and demonstrated end-to-end ownership.Agent orchestration: Google ADK, LangGraph, LangChain, LlamaIndex, or comparable frameworksContext engineering: RAG, MCP, knowledge graphs, tool use, memory, and retrieval systemsAI evaluation: offline and online evaluations, test datasets, regression testing, observability, and human reviewLanguage models ...

Viridien (www.viridiengroup.com) is an advanced technology, digital and Earth data company that pushes the boundaries of science for a more prosperous and sustainable future. With our ingenuity, drive and deep curiosity we discover new insights ...

extend platform components—APIs, tooling, and bespoke logic Architecture & Standards Architect robust, scalable, and compliant Agentic AI solutions across industries Lead multi-agent orchestration, RAG pipelines, and LLM/SLM integration design Champion observability, telemetry, and auditable AI standards Build and maintain reusable frameworks and asset libraries Team & Product Help …/Vue, SQL, REST/GraphQL DevOps proficiency: Docker, Kubernetes, CI/CD, and major cloud platforms Expertise in LLMs, Prompt Engineering, Vector DBs, RAG pipelines, and Agentic orchestration frameworks Agentic/Integrations: MCP, Salesforce/SAP/Other Excellent communication with both technical and executive stakeholders Mentorship capability ...

build what’s next - together! Role Overview We're hiring a Principal AI Architect to design and architect next-generation AI solutions that transform how enterprises plan and make decisions. You'll lead the architecture for GenAI and Agentic AI systems at Anaplan, working at the intersection … concepts into clear insights for diverse engineering and business stakeholders. Knowledge of Model Context Protocol (MCP) and agent communication standards Experience with vector databases, RAG architectures, and semantic search systems Familiarity with cloud platforms (AWS, Azure, GCP) and their AI services Experience in SaaS or enterprise software companies Our Commitment ...

join us and let’s build what’s next - together!Role OverviewWe're hiring a Principal AI Architect to design and architect next-generation AI solutions that transform how enterprises plan and make decisions. You'll lead the architecture for GenAI and Agentic AI systems at Anaplan, working … concepts into clear insights for diverse engineering and business stakeholders.DesirableKnowledge of Model Context Protocol (MCP) and agent communication standardsExperience with vector databases, RAG architectures, and semantic search systemsFamiliarity with cloud platforms (AWS, Azure, GCP) and their AI servicesExperience in SaaS or enterprise software companiesOur Commitment to Diversity, Equity, Inclusion ...

early, and drive progress without being pushedConsulting or client-facing delivery experience is a strong advantageExposure to GenAI applications in decisioning — personalised content generation, AI-driven offer selectionPreferredExperience evaluating purpose-built decisioning solutions and contributing to capex/opex business casesFamiliarity with real-time streaming technologies … Required — Technical SkillsAdvanced Python — writing clean, production-grade code, not just scripts (OOP, async, packaging, testing)Generative AI & LLM development — prompt engineering, fine-tuning, RAG pipelines, context window managementAgentic AI frameworks — LangChain, LangGraph, AutoGen, or similar; building multi-step autonomous workflowsMachine Learning — model development, training, evaluation, and deploymentAPIs & backend development ...

Lead the implementation of AI-enabled applications and platform capabilities. Establish reusable patterns, frameworks, and best practices for AI engineering. Design and oversee LLM, RAG, and Agentic AI integrations within enterprise environments. Collaborate with architects and engineering teams to ensure scalable, secure, and maintainable solutions. Define standards for AI observability … applications on Azure, AWS, or GCP. Strong knowledge of Kubernetes, Microservices, APIs, Event‐Driven Architecture, and DevOps practices. Hands‐on experience with LLM integration, RAG architectures, AI orchestration frameworks, and Agentic AI solutions. Experience with AI frameworks and tools such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or equivalent. #J ...

/CD Tooling, Cloud Architecture Design, Cloud-native AI Platforms, Docker, GCP, Generative AI, Innovation Leadership, Kubernetes, LangChain, LlamaIndex, MLOps, MLflow, Orchestration Frameworks, RAG Pipelines, Stakeholder ManagementSenior AI Engineer - Consulting Office location to choose from: Glasgow, London or Manchester Hybrid Working – 1-2 days per week in the office … 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 ...

platforms and LLM-powered applications.Own end-to-end engineering lifecycle: architecture, build, deployment, and optimisation of AI services.Drive adoption of modern AI patterns including RAG, agent orchestration, and event-driven workflows.Ensure production readiness through observability, resilience engineering, and cost optimisation.Agentic AI & OrchestrationOversee development of multi-agent systems using frameworks such … Azure OpenAI, AI Foundry, Cognitive Services).Proven expertise in building and scaling distributed, cloud-native systems (AKS, microservices, APIs).Experience with LLM application design: RAG, prompt engineering, orchestration frameworks.Proficiency in modern programming and automation (Python, PowerShell, REST APIs, IaC).Understanding of data platforms (CosmosDB, SQL, Redis) and event-driven architectures.Experience ...

Genixbit in London is seeking an AI Engineer to fine-tune open-source models for domain tasks, improve deployment pipelines, and develop context management and semantic search solutions. The role requires hands-on experience with ...

GenixBit Labs Pvt. Ltd. is seeking an AI Engineer in London specializing in LLM fine-tuning and Generative AI. You will work on optimizing and tailoring models for specific applications, ensuring high performance in low ...

articulate the business problem behind the technology you're building. It would be advantageous if you also have experience with: RAG (Retrieval-Augmented Generation) Agentic workflows and tool use Vector databases/search and embeddings LLM APIs from multiple providers AI evaluation frameworks ...