701 to 725 of 878 Retrieval-Augmented Generation Jobs in the UK

systems. Strong technical understanding of AI/ML and generative AI systems, including model development, model evaluation, data pipelines, embeddings, retrieval-augmented generation, prompt engineering, monitoring, drift, robustness, explainability, and safety testing. Demonstrated ability to assess technical AI risks and recommend practical controls ...

Experience in cybersecurity, email security, or adjacent enterprise SaaS domains preferred.* Familiarity with AI/ML concepts including prompt engineering, model evaluation, retrieval-augmented generation, and agent orchestration frameworks is valuable but can be developed in-role.* Prior experience in a developer enablement, developer ...

have Experience building, deploying, and maintaining machine-learning pipelines in production (the maintenance matters as much as the building). Experience with Retrieval-Augmented Generation, and with vector or graph databases. Familiarity with a modern data stack: Databricks, dbt, DLT, Unity Catalog or similar. ...

routing, rate limiting, cost management, modelselectionand version control across multiple model providers. AI solution design Design retrieval and reasoning architectures including RAG, corrective RAG (CRAG), and agentic patterns, selecting the right approach for a given business problem. #J-18808-Ljbffr ...

production, and guide delivery with senior client teams. Based in London or other major UK hubs, you will lead hands-on engineering, contribute to RAG pipelines and eval frameworks, and mentor engineers while embedding GenAI and governance into client journeys. #J-18808-Ljbffr ...

translate business needs into concrete AI solutions. This role emphasizes collaboration, agile practices, and staying at the forefront of AI research, including LLMs, RAG, and responsible AI. The position supports flexible work options and global opportunities within Valtech’s value-driven culture. #J-18808-Ljbffr ...

outcomes can be achieved. You will work across customer‐facing AI use cases including personalisation, customer decisioning, customer service agents, retrieval‐augmented generation solutions and agentic workflows. This is a senior role, but it remains technical. You will need to review architectures, challenge design … teams and ensure solutions are ready for production. What You Will Do Review and challenge solution architectures, covering model selection, retrieval‐augmented generation, agentic workflows, evaluation frameworks, guardrails, scalability and cost. Identify technical and delivery risks early, including data quality issues, integration complexity, performance ...

pipelines, entity extraction, classification, ranking, search, recommendation, data quality, knowledge graph enrichment, predictive analytics, LLM-based systems, Gen AI Agents, Multi Agent systems and RAG where relevant. You will work closely with product, engineering, content, domain experts, and business stakeholders to deliver scalable, measurable, and production-ready data science solutions … chemical entities, drugs, genes, diseases, clinical trials, safety data, publications, patents, metadata, and ontologies. Guide the use of modern AI approaches, including embeddings, LLMs, RAG, prompt-based workflows, and GenAI evaluation, where they add clear customer and business value. Partner with engineering to ensure solutions are robust, scalable, maintainable ...

closely with engineers to translate validated approaches into scalable, customer-facing solutions. Key Responsibilities: Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies, patent search). Define agentic workflows and reasoning strategies for multi-step IP tasks. Develop retrieval strategies, including hybrid search (semantic … Strong experience designing and running experiments, including model evaluation and iteration. Strong coding skills in Python. Experience with generative AI techniques (e.g., prompt engineering, RAG). Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases. Experience designing agentic workflows and reasoning strategies, with hands ...

closely with engineers to translate validated approaches into scalable, customer-facing solutions. Key Responsibilities: Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies, patent search).Define agentic workflows and reasoning strategies for multi-step IP tasks. Develop retrieval strategies, including hybrid search (semantic + … Strong experience designing and running experiments, including model evaluation and iteration. Strong coding skills in Python. Experience with generative AI techniques (e.g., prompt engineering, RAG).Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases. Experience designing agentic workflows and reasoning strategies, with hands-on experience ...

closely with engineers to translate validated approaches into scalable, customer-facing solutions. Key Responsibilities: Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies, patent search). Define agentic workflows and reasoning strategies for multi-step IP tasks. Develop retrieval strategies, including hybrid search (semantic … Strong experience designing and running experiments, including model evaluation and iteration. Strong coding skills in Python. Experience with generative AI techniques (e.g., prompt engineering, RAG). Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases. Experience designing agentic workflows and reasoning strategies, with hands ...

closely with engineers to translate validated approaches into scalable, customer-facing solutions. Key Responsibilities: Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies, patent search). Define agentic workflows and reasoning strategies for multi-step IP tasks. Develop retrieval strategies, including hybrid search (semantic … Strong experience designing and running experiments, including model evaluation and iteration. Strong coding skills in Python. Experience with generative AI techniques (e.g., prompt engineering, RAG). Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases. Experience designing agentic workflows and reasoning strategies, with hands ...

Tech Lead level, with the ability to be both highly technical and an effective people manager Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses) and taking them to production or in platforming (LLM or MCP gateway, agentic runtime, auth, data retrieval, eval … About the Team Our AI Strategy and Innovation team shapes Moody's product ecosystem through AI, data, and strategic partnerships to deliver next-generation solutions. The team embeds AI across product strategy using large language models, agentic platforms, and advanced analytics to enhance decision-making and client outcomes. ...

Tech Lead level, with the ability to be both highly technical and an effective people manager Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses) and taking them to production or in platforming (LLM or MCP gateway, agentic runtime, auth, data retrieval, eval … About the Team Our AI Strategy and Innovation team shapes Moody's product ecosystem through AI, data, and strategic partnerships to deliver next-generation solutions. The team embeds AI across product strategy using large language models, agentic platforms, and advanced analytics to enhance decision-making and client outcomes. ...

Tech Lead level, with the ability to be both highly technical and an effective people manager Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses) and taking them to production or in platforming (LLM or MCP gateway, agentic runtime, auth, data retrieval, eval … technical direction Our AI Strategy and Innovation team shapes Moody's product ecosystem through AI, data, and strategic partnerships to deliver next-generation solutions. The team embeds AI across product strategy using large language models, agentic platforms, and advanced analytics to enhance decision-making and client outcomes. ...

Designing APIs, services and integrations to connect AI capabilities with wider enterprise systems. Building agentic AI applications, including multi-agent workflows and orchestration. Developing RAG solutions using vector search, enterprise data and retrieval techniques. Writing clean, maintainable and well-tested production code. Working with CI/CD pipelines … building AI-enabled applications using technologies such as Azure AI, Microsoft AI Foundry, Azure OpenAI, Semantic Kernel, Agent Framework or similar. Understanding of RAG, LLMs, vector search and agentic AI concepts. Experience integrating applications with APIs, cloud services and enterprise systems. Strong understanding of DevOps, CI/CD, source control ...

tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams. Applies knowledge … multiple modern programming languages including Python, Golang, TypeScript and similar technologies in an AWS/Cloud environment. Experience in the use of GPT, LLM, RAG, Gen AI, Prompt Engineering related technologies Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages ...

reliability, innovation and engineering excellence. Your impact As a Technical Leader, you will drive the architectural vision and implementation of our next-generation AI-powered Production Intelligence platform. You will combine Site Reliability Engineering practices with modern agentic AI (reusable Skills, Model Context Protocol (MCP), and LLM tooling … management, and automated RCA. Preferred Qualifications AI & Agentic Systems: Hands‐on experience building LLM pipelines, AI Agents, Model Context Protocol (MCP) servers/clients, RAG architectures, and evaluation frameworks. Observability & Telemetry: Experience with OpenTelemetry (OTel), Prometheus, Grafana, Splunk, ThousandEyes, or distributed tracing systems. Cloud & Infrastructure: Expertise in public cloud providers ...

efficiency Developing reusable AI capabilities and accelerators Supporting analysis, reporting and knowledge management initiatives Technical Responsibilities Python development AI agent orchestration LLM applications and RAG solutions API integrations Data pipelines Cloud-based development Application development Workflow automation What We're Looking For Essential 2-4 years' software engineering experience Strong … automation tooling Experience delivering real-world software solutions Strong problem-solving ability Excellent communication skills Highly Desirable AI Agents/Agentic AI experience RAG architectures Data engineering experience Cloud platforms (Azure, AWS or GCP) Modern application development experience Consultancy or client-facing experience Interest in emerging AI technologies Who This ...

multi-modal LLMs (text, image, audio, video), design agentic workflows enabling AI agents to interact with data sources and APIs using prompt engineering and RAG, optimise and deploy large language and multi-modal models with a focus on performance and latency and build scalable MLOps pipelines and full-stack applications … Langsmith, MCP (Model Context Protocol), bias mitigation techniques Apply now to find out more about this Backend Software Engineer/Developer (Python LLM MLOps RAG MCP) opportunity. ...

for. What you'll be working on as an AI Engineer - LLM & Agentic Systems: Designing and building AI agents and agentic workflows - combining LLMs, RAG, reasoning, memory and tool orchestration to solve real, complex business problems. Owning delivery end-to-end - from initial exploration through to production deployment, integration … with clear, real-world examples you can speak to confidently. Hands-on experience building AI agents including tool use, orchestration and multi-step reasoning - RAG systems that actually deliver, not just proofs of concept. Strong Python skills and solid machine learning foundations - able to write clean, production-grade code with ...

build business cases, and define practical implementation roadmaps. Provide technical leadership across AI technologies Lead across modern AI architectures, Generative AI, Agentic AI, LLMs, RAG, Data Platforms, Cloud AI Services, and enterprise integration patterns. Remain hands‐on where required Lead solution architecture, technical assurance, innovation leadership, and support the resolution … consultants, architects, data specialists, and AI engineers, fostering innovation and continuous learning. Essential skills AI technical depth Generative AI, Agentic AI, Machine Learning, LLMs, RAG, MLOps, Enterprise AI Architecture, AI Risk Management & Compliance. Governance and operating models AI Strategy, AI Governance, Responsible AI Frameworks, and AI Operating Models. Data foundations ...

Solution Delivery Lead the design, development and deployment of AI-integrated applications using modern full-stack technologies. Build features powered by LLMs, agentic workflows, RAG patterns and MCP integrations. Work directly with customers to shape requirements and translate them into working software. Integrate Azure AI services such as Azure OpenAI …/Node.js, .NET/C#, Python/FastAPI). Proven background delivering production software in client-facing environments. Experience with LLM integration, prompt engineering, RAG or agentic AI development. Familiarity with AI-assisted development tools (GitHub Copilot, Claude, Cursor). Hands-on experience with Azure cloud services and CI/ ...

including data ingestion and modelling, backend services and APIs, AI orchestration, frontend experiences, deployment, and operations. Design and build production-grade AI features, including RAG across structured and unstructured investment data, agentic workflows, document intelligence, and AI-generated analytics. Build intuitive, information-dense interfaces for investment professionals, including analytical grids … React, advanced SQL, and complex data modelling, working with both structured and unstructured data. Proven applied AI/LLM experience, shipping production solutions using RAG, embeddings/vector search, agentic workflows, evaluation frameworks, and guardrails. Hands-on cloud and infrastructure expertise across Azure and Kubernetes (AKS), including containerisation ...

Kubernetes, and cloud-native infrastructure. Design and deploy scalable batch and real-time ML pipelines supporting customer-facing applications. Develop and operationalise LLM applications, RAG systems, and Generative AI capabilities for content understanding, summarisation, classification, and recommendation use cases. Build evaluation frameworks and observability solutions to monitor model quality, reliability … Intelligence, Statistics, Data Science, or a related STEM field. Experience applying Generative AI and LLMs to customer-facing products and designing, building, or scaling RAG systems. Experience in search, ranking, recommendations, personalisation, content intelligence, moderation, NLP, computer vision, or related AI domains. Experience with Airflow or comparable workflow orchestration platforms. ...