476 to 500 of 876 Retrieval-Augmented Generation Jobs in the UK

practice Basic Qualifications Engineering experience with cloud-native systems (APIs, microservices, containerization, serverless). Deepexpertisein designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments. Experience with AI platforms OpenAI, Claude, Vertex AI, plus open-source models including building abstraction layers to manage multi-provider pipelines. ...

practice Basic Qualifications Engineering experience with cloud-native systems (APIs, microservices, containerization, serverless). Deepexpertisein designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments. Experience with AI platforms OpenAI, Claude, Vertex AI, plus open-source models including building abstraction layers to manage multi-provider pipelines. ...

Microsoft, Oracle, or similar platforms.* Background in change management, organisational design, or enterprise transformation* Experience with AI/ML concepts beyond LLMs, including NLP, RAG architectures, and model evaluation frameworks* A get-things-done mindset with strong bias for action — comfortable operating in unstructured fast moving environmentsUnleash Your PotentialWhen ...

experience building and deploying production-grade software in Python; you write clean, testable, observable, scalable code You've built and deployed highly performant RAG and agentic applications, including agents that plan and execute multi-step tasks using patterns like ReAct or Plan-and-Execute You're deeply familiar with ...

experience building and deploying production-grade software in Python; you write clean, testable, observable, scalable code You've built and deployed highly performant RAG and agentic applications, including agents that plan and execute multi-step tasks using patterns like ReAct or Plan-and-Execute You're deeply familiar with ...

experience building and deploying production-grade software in Python; you write clean, testable, observable, scalable code You've built and deployed highly performant RAG and agentic applications, including agents that plan and execute multi-step tasks using patterns like ReAct or Plan-and-Execute You're deeply familiar with ...

hands-on experience building and deploying production-grade software in Python; you write clean, testable, observable, scalable codeYou've built and deployed highly performant RAG and agentic applications, including agents that plan and execute multi-step tasks using patterns like ReAct or Plan-and-ExecuteYou're deeply familiar with ...

essential. AI and ML platform architecture: experience designing AI/ML data infrastructure - including feature stores, model training pipelines, inference serving, and GenAI/RAG architectures grounded in proprietary content. Lakehouse and modern data platform design: strong knowledge of open table formats (Apache Iceberg, Delta Lake), zone architecture (landing, cleansed ...

such as Microsoft, Oracle, or similar platforms.Background in change management, organizational design, or enterprise transformationExperience with AI/ML concepts beyond LLMs, including NLP, RAG architectures, and model evaluation frameworksA get-things-done mindset with strong bias for action — comfortable operating in unstructured fast moving environmentsUnleash Your PotentialWhen you join ...

solution delivery across client engagements — setting the bar for what production-ready looks like Review and challenge solution architectures end-to-end: LLM selection, RAG pipeline design, agentic workflow logic, evaluation frameworks, guardrails, cost modelling, and scalability Define and enforce the standards that separate a working POC from a deployable … build the talent to sustain it What You Will Bring Required — Proven GenAI Delivery A track record of shipping GenAI solutions into production — RAG pipelines, agentic workflows, LLM-powered applications, or multimodal systems — not just designing or advising on them Deep hands-on experience with the full GenAI delivery stack ...

Model programme for a central government department. Where the Lead Technical Architect sets direction, you turn it into working, production-grade systems - semantic search, RAG pipelines, and broader generative AI capability - integrated into complex Legacy and multi-cloud environments handling high-volume, sensitive public sector data. You'll work inside … eventually run these systems without long-term reliance on external suppliers. Key Responsibilities Hands-On Build & Delivery Design, build, and ship production AI components - RAG pipelines, retrieval and embedding infrastructure, orchestration logic, and integration layers - writing high-quality, tested, maintainable code and staying close to implementation rather than ...

Model programme for a central government department. Where the Lead Technical Architect sets direction, you turn it into working, production-grade systems - semantic search, RAG pipelines, and broader generative AI capability - integrated into complex Legacy and multi-cloud environments handling high-volume, sensitive public sector data. You'll work inside … eventually run these systems without long-term reliance on external suppliers. Key Responsibilities Hands-On Build & Delivery Design, build, and ship production AI components - RAG pipelines, retrieval and embedding infrastructure, orchestration logic, and integration layers - writing high-quality, tested, maintainable code and staying close to implementation rather than ...

solving some of the most exciting challenges and problem solving in enterprise AI rollout, spanning enterprise data pipelines, multi‐agent orchestration/workflows and RAG/SLM finetuning. Responsibilities Lead the technical solution design and implementation of large‐scale Agentic and Knowledge AI solutions for key enterprise clients. … solution delivery through reusable assets, frameworks, and documentation. Champion observability, monitoring, versioning and telemetry to ensure trustworthy and auditable AI agents. Stay current on RAG, LLM/SLM advancements, Agentic AI tooling, vector/graph databases, retrieval optimizations, multi‐modal systems, evaluation frameworks, GPU/Infra trends, fine ...

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 ...

building the next generation of AI-native engineering talent engineers who use AI as a core part of how they work, not as an add-on. As an AI Engineer (Software), you will design, build, and ship production-grade software across the full stack, using AI-assisted tooling … improve AI-generated outputs; understanding of AI limitations and responsible use Familiarity with agentic system concepts — awareness of orchestration frameworks (LangChain, LangGraph, or equivalent), RAG pipelines, and how full-stack applications connect to agent-based architecture; production experience preferred, conceptual understanding required #LI-EU About Accenture Accenture is a leading ...

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 ...

complex datasets, including time series data, from various sources (web APIs, databases, real-time streams). Leverage Generative AI platforms and frameworks agents, RAG, prompt and context engineering, evaluations and AI SDLC to deliver novel capabilities for the trading organisation. Tap into expertise in AWS cloud services (S3, Redshift … Selenium, Beautiful Soup and Requests, and machine learning libraries such as TensorFlow and PyTorch). Generative AI techniques including agents, skills, prompt engineering, RAG, AI SDLC, context engineering and evaluations. Mastery of SQL (including advanced optimisation techniques) and experience with relational databases (PostgreSQL preferred), including data modelling and design skills. ...

complex datasets, including time series data, from various sources (web APIs, databases, real-time streams). Leverage Generative AI platforms and frameworks agents, RAG, prompt and context engineering, evaluations and AI SDLC to deliver novel capabilities for the trading organisation. Tap into expertise in AWS cloud services (S3, Redshift … Selenium, Beautiful Soup and Requests, and machine learning libraries such as TensorFlow and PyTorch). Generative AI techniques including agents, skills, prompt engineering, RAG, AI SDLC, context engineering and evaluations. Mastery of SQL (including advanced optimisation techniques) and experience with relational databases (PostgreSQL preferred), including data modelling and design skills. ...

read-only pulls and progressing to bidirectional integration.**AI & Agentic Workflows*** Design, deploy and orchestrate agentic AI workflows using frameworks such as LangGraph; implement RAG pipelines, fine-tuned models and vector database integrations within the assigned business domain.* Operate the end-to-end delivery toolchain (AWS, GitLab, Docker, CI/… pipelines, REST/gRPC APIs and microservices architecture; identity and access management with OIDC/SAML and Azure Entra ID.* Experience with LLMs, RAG systems, prompt engineering and AI evaluation frameworks; familiarity with MLOps, model deployment and AI observability/guardrails; working use of AI-assisted development tools (e.g. Claude ...

Python and SQL, with production code ownership. Not familiarity. Demonstrable experience integrating large language models into production systems — prompt and context design, retrieval-augmented generation, structured output, and handling failure gracefully. Practical experience with at least one major cloud AI platform (Azure ...

Python and SQL, with production code ownership. Not familiarity. Demonstrable experience integrating large language models into production systems — prompt and context design, retrieval-augmented generation, structured output, and handling failure gracefully. Practical experience with at least one major cloud AI platform (Azure ...

privacy, cross-border data residency and audit requirements).* **AI Foundations:** Experience designing agentic or AI-enabled solutions, including patterns such as retrieval-augmented generation, tool and API integration, evaluation and human-in-the-loop design, would be a significant advantage, though ...

consistency, accuracy and usefulness of their outputs. Design AI-enabled solutions using modern approaches including Large Language Models (LLMs), Retrieval Augmented Generation (RAG), workflow automation, knowledge retrieval and AI-assisted user experiences. Apply prompt-as-code, prompt testing and evaluation-led development … discovery and requirements gathering through implementation and adoption. Strong understanding of modern AI technologies and patterns including Large Language Models, Retrieval Augmented Generation, AI agents, evaluation frameworks and model orchestration patterns. Practical experience applying prompt engineering, context engineering, prompt-as-code and versioning practices ...

will play a key role in shaping how AI, agents, data, and ontology-driven business context become foundational capabilities across the next generation of Infor Manufacturing solutions. A Typical Day in the Life Includes: Defining the AI architecture, standards, and technical strategy for MES and the Manufacturing portfolio. … practices and technologies. Proven experience designing and delivering production AI solutions using Large Language Models (LLMs). Experience with Retrieval Augmented Generation (RAG), agentic architectures, AI orchestration frameworks, and tool-based AI systems. Experience integrating AI capabilities into enterprise software products. Experience designing APIs ...