701 to 725 of 890 Retrieval-Augmented Generation Jobs in England

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 ...

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 ...

team to join the bank with specific AI related skills. Key criteria: Experience in AI-driven and AI-assisted testing, including GenAI, RAG-based systems, intelligent automation, and tools such as GitHub Copilot, Amaz click apply for full job details ...

software development. The ideal candidate will be proficient in Python and have hands-on experience with Generative AI and Retrieval Augmented Generation solutions, particularly in the context of software testing. This role requires a blend of technical expertise, innovative thinking, and effective communication skills … quality assurance solutions. Responsibilities: Develop and implement AIML solutions focused on enhancing software testing processes. Utilize Generative AI and Retrieval Augmented Generation techniques to improve testing efficiency and accuracy. Work with Large Language Models (e.g., GPT, Claude) to create and optimize AIML applications. Leverage ...

direct pathway to the Forward Deployed Engineer programme. Key Responsibilities Design and build production-grade agentic systems end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning … depth, not tutorial level Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering LLMOps fundamentals: eval harness design, prompt versioning, and production observability Cloud-native engineering maturity: Kubernetes ...

Curve Maintain a current and deep understanding of the evolving Generative AI and Agentic AI landscape — frontier models, AI patterns, prompt engineering, fine‐tuning, RAG architectures, and multi‐agent orchestration. Translate complex technical concepts into clear business value propositions specific to Fund Services operations and clients. Fund Services is building … cloud architectures, distributed systems, and modern software development practices Deep understanding of the Generative AI ecosystem — frontier models, AI patterns, prompt engineering, fine‐tuning, RAG, and agentic architectures Proven ability to move from problem identification to working prototype at pace — with a portfolio of real things built, not just planned ...

Curve Maintain a current and deep understanding of the evolving Generative AI and Agentic AI landscape — frontier models, AI patterns, prompt engineering, fine-tuning, RAG architectures, and multi-agent orchestration. Translate complex technical concepts into clear business value propositions specific to Fund Services operations and clients.Fund Services is building next … including cloud architectures, distributed systems, and modern software development practicesDeep understanding of the Generative AI ecosystem — frontier models, AI patterns, prompt engineering, fine-tuning, RAG, and agentic architecturesProven ability to move from problem identification to working prototype at pace — with a portfolio of real things built, not just plannedExperience working ...

build and deploy enterprise-grade AI solutions across an Enterprise Knowledge Base (EKB). This is a hands-on role focused on GenAI, LLMs, RAG and Agentic AI, taking solutions from prototype through to production. You'll work across AI, data and engineering teams to build intelligent retrieval, knowledge discovery and automation capabilities. Key Responsibilities Build production-grade GenAI, LLM, RAG and Agentic AI solutions Develop AI Agents and Multi-Agent Systems Work with LangChain, LangGraph and MCP Build intelligent retrieval using Embeddings, Vector Databases and Semantic Search Apply Prompt & Context Engineering Integrate ...

Developing AI solutions that can reason, retrieve information, make decisions and take actions Working with business data to develop intelligent applications and automation Developing RAG, vector search, embeddings and knowledge-based AI solutions Evaluating new LLMs, AI frameworks and emerging technologies Taking AI concepts from initial idea through to production … following: Agentic AI/AI Agents LLM application development OpenAI, Azure OpenAI, Anthropic, Gemini or similar LLM orchestration and tool/function calling RAG and retrieval-based AI Vector databases and embeddings AI workflow automation Python, C# and/or TypeScript APIs and system integration SQL/databases ...

partnering 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 + lexical … based modeling.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 applying agent ...

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 managerHands-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 tooling … technical directionAbout the TeamOur 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. ...

will be an on-site role.In this role, you will have the opportunity to:Design and deliver end-to-end LLM-powered applications, including RAG systems and agent workflows.Transform prototypes into reliable, scalable production services with deployment, monitoring, and failure handling.Integrate and operate external model APIs, managing constraints such … essential requirements of the job include:Strong software engineering capability, primarily in TypeScript and Python with backend and API development skills.Expertise in GenAI systems: RAG, prompt engineering, LLM integration, and agentic workflows.Cloud and infrastructure knowledge, including deployment, containerization, and CI/CD practices.Understanding of machine learning fundamentals, including model behavior ...

site role. In this role, you will have the opportunity to: Design and deliver end-to-end LLM-powered applications, including RAG systems and agent workflows. Transform prototypes into reliable, scalable production services with deployment, monitoring, and failure handling. Integrate and operate external model APIs, managing constraints such as latency … requirements of the job include: Strong software engineering capability, primarily in TypeScript and Python with backend and API development skills. Expertise in GenAI systems: RAG, prompt engineering, LLM integration, and agentic workflows. Cloud and infrastructure knowledge, including deployment, containerization, and CI/CD practices. Understanding of machine learning fundamentals, including ...

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 ...

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 ...

team focused on reliability, innovation and engineering excellence.Your impactAs 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 … traces), incident management, and automated RCA.Preferred QualificationsAI & 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 ...

.NET, Python, TypeScript, JavaScript, React, Go, Ruby, Scala, R, and SQL Leveraged AI‐assistive development tools for tasks like scaffolding, refactoring, debugging, test generation, and documentation Experience building or integrating AI/ML‐powered features into products or systems (e.g., recommendation engines, NLP models, computer vision, predictive analytics … platforms, and infrastructure that other teams build on Data Engineering: including platforms like Databricks for data processing and analytics Delivering production agentic systems, including RAG pipelines, vector search, and agentic frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, and n8n DevSecOps & DevOps MLOps Infrastructure as Code Building a truly diverse, equitable ...

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 … Langfuse, Langsmith, MCP (Model Context Protocol), bias mitigation techniquesApply now to find out more about this Backend Software Engineer/Developer (Python LLM MLOps RAG MCP) opportunity. ...

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. ...

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/ ...

dependency mapping, service impact, and fault propagation. Work with AI/LLM engineers to provide high-quality features, embeddings, metadata, and contextual datasets for RAG and agentic AI systems. Define network data quality rules, correlation logic, and entity resolution methods. Create reusable analytical models for RAN, Core, IP/MPLS … assessment. Experience with graph analytics, entity relationship mapping, or knowledge graph concepts. Understanding of LLMs and how structured data can support AI agents and RAG systems. Experience with BigQuery or similar data warehouse/analytics platforms. Required Technical Skills Python. Statistics and ML basics. Network KPI modelling. RAN, Core ...