501 to 525 of 886 Retrieval-Augmented Generation Jobs in England

Azure, including SaaS and PaaS offerings. Hands-on experience building and deploying with modern AI, including large language models and agentic AI (prompt engineering, RAG, tool and function calling, orchestration), on the Microsoft AI stack such as Azure OpenAI, Azure AI Foundry and Azure AI services. Proven experience of technical ...

commercial environmentStrong full-stack skills in TypeScriptFrontend skills with Next.js or React to build an interface for engineersStrong AI knowledge — LLMs, embeddings, MCPs, RAG, evals, agentic platformsExperience of building infrastructure to support your systems in production using IaC, k8s or lambda functionsSelf-starter who takes ownership end-to-end — from ...

especially MS SQL)REST APIs or GraphQLContainers and cloud platforms (e.g., Azure)Experience building modular systems with continuous deliveryExperience building AI-powered features (e.g., RAG systems, LLM integrations)Degree in Computer Science or equivalent experienceEducationBachelor’s Degree (Computer Science or engineering preferred) or equivalent work experienceOptimizely is committed ...

must demonstrate differentiated, hands-on Agentic AI and GenAI expertise: 1/Proven experience architecting and building agentic AI systems - including multi-agent orchestration, RAG pipelines, and prompt engineering - not theoretical familiarity but demonstrated delivery of working prototypes and customer-facing demos. 2/Proficiency using AI-powered coding assistants ...

wider organisation. About the role: This position serves as a subject matter expert for Machine Learning Engineering, supporting production AI/ML, LLM/RAG, and agentic workflow capabilities for legal content products. In addition to writing code on complex systems, this position provides technical direction on architecture, MLOps, responsible … including model lifecycle management, CI/CD, testing, monitoring, release management, observability, and operational support. Practical experience with LLM-based capabilities, including retrieval-augmented generation, semantic search, embeddings, prompt design, evaluation, guardrails, and observability. Experience with agentic workflows, tool orchestration, and multi-step ...

covers the full AI/ML engineering lifecycle, from discovery to deployment and monitoring. Responsibilities include Designing and implementing agentic systems using techniques spanning RAG, grounding, prompt engineering, and orchestration on a GCP‐first stack. Building and maintaining production ML pipelines and services for non‐GenAI use cases (e.g. recommender … Terraform), experiment tracking, model registry, and monitoring. Proven experience deploying and operating ML systems in production (batch and real‐time). Familiarity with RAG architectures, prompt engineering, guardrails and evaluation techniques. Previous experience developing agentic capabilities, such as agent skills, MCP servers, tool usage. Strong grasp of security, privacy ...

across a range of AI and cloud projects. Responsibilities will include: Designing and delivering Generative AI and Machine Learning solutions Building applications using LLMs, RAG frameworks and AI orchestration tools Working directly with clients to understand business challenges and define AI-driven solutions Leading architecture and engineering decisions across Azure … experience building AI-powered applications and deploying them into production Software Engineering or Product Engineering background Strong Python development skills Experience working with LLMs, RAG architectures and modern AI frameworks Multi-cloud experience across Azure, AWS and GCP Strong understanding of cloud-native architectures and scalable application design Experience with ...

across a range of AI and cloud projects. Responsibilities will include: Designing and delivering Generative AI and Machine Learning solutions Building applications using LLMs, RAG frameworks and AI orchestration tools Working directly with clients to understand business challenges and define AI-driven solutions Leading architecture and engineering decisions across Azure … experience building AI-powered applications and deploying them into production Software Engineering or Product Engineering background Strong Python development skills Experience working with LLMs, RAG architectures and modern AI frameworks Multi-cloud experience across Azure, AWS and GCP Strong understanding of cloud-native architectures and scalable application design Experience with ...

large and 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 … such as 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.Extensive ...

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. ...

Python-based development when needed, particularly during critical delivery phases or proof-of-concept work.Support the design and delivery of Generative AI solutions, including RAG architectures, prompt engineering, and integration with Azure AI services (e.g., Azure OpenAI, Azure AI Search).Ensure robust MLOps practices are followed, including model versioning, testing … MLflow for experiment tracking and model management, and Spark-based data processing.Familiarity with Generative AI concepts and tooling, including working with LLMs, prompt engineering, RAG patterns, and vector search.A solid understanding of MLOps principles, including CI/CD for models, automated testing, and monitoring of deployed solutions.Cloud platform experience, preferably ...

copilots, assistants, knowledge-search experiences, and agentic workflows, as reliable, production-grade systems rather than demos. Architect and implement end-to-end retrieval-augmented generation pipelines, including parsing, ingestion, chunking strategy, embeddings, vector storage, retrieval, and prompt management. Build agents and agentic … shipping LLM-powered applications, including advanced prompt engineering, retrieval, agent development, and evaluation. Demonstrated experience designing and building end-to-end RAG pipelines and integrating LLM solutions with real systems. Strong understanding of system design, APIs, distributed-systems concepts, and cloud-native development, with a track record ...

Join us at the forefront of applied AI innovation and help build the next generation of agentic AI applications at one of the world’s largest banks. You will bridge cutting-edge AI capabilities with enterprise-grade engineering to deliver measurable impact across Markets Operations. You will collaborate … machine learning, generative AI, or agentic applications, including integration with enterprise systems and workflowsStrong understanding of LLM application patterns, including prompt engineering, retrieval-augmented generation, tool calling, context management, evaluation, and guardrailsExperience with RESTful API design, development, and integration, including frameworks such as FastAPIExperience ...

rate limiting, cost management, model selection and 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. Architect agent harnesses and their components — planning, memory, tool … understanding of how AI integrates with major operational systems such as SAP, Salesforce and ServiceNow. Hands-on knowledge of agentic AI, LLM gateways, MCP, RAG/CRAG, agent harnesses, evaluations and guardrails, and AI observability. Demonstrable experience designing and leading data & AI transformation programmes, and building high-performing teams ...

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 ...

research and make investment decisions. Working closely with Portfolio Managers, Research Analysts, Sustainability teams, Architects and Engineers, you will define and deliver next-generation capabilities leveraging Generative AI, agentic workflows and advanced analytics to create measurable business value across global investment teams. Key Responsibilities Own the vision, roadmap … investment data, holdings, benchmarks and fund look-through capabilities. Experience delivering AI-powered solutions, including Large Language Models (LLMs), Retrieval Augmented Generation (RAG), AI assistants, agentic workflows and knowledge discovery platforms. Demonstrated product management experience, including product strategy, roadmap development, prioritisation, backlog management ...

equivalentsPrompt engineering, context design and agentic workflow frameworksEvaluation harnesses, evaluation datasets and automated test suites for AI outputsRetrieval-augmented generation (RAG), vector search, embeddings and retrieval pipelines (desirable)LLM orchestration frameworks (LangChain, Semantic Kernel or equivalents – desirable)Technical and Professional ExpertiseStrong software engineering background … GitHub Copilot, Cursor or equivalents, with a practical view of where they help and where they mislead.Preferred Qualifications and ExperienceRetrieval-augmented generation, agentic workflows, tool use or fine-tuning in production settings.Experience with LLM APIs, orchestration frameworks, vector search, embeddings, retrieval pipelines, evaluation datasets ...

equivalentsPrompt engineering, context design and agentic workflow frameworksEvaluation harnesses, evaluation datasets and automated test suites for AI outputsRetrieval-augmented generation (RAG), vector search, embeddings and retrieval pipelines (desirable)LLM orchestration frameworks (LangChain, Semantic Kernel or equivalents – desirable)Technical and Professional ExpertiseStrong software engineering background … GitHub Copilot, Cursor or equivalents, with a practical view of where they help and where they mislead.Preferred Qualifications and ExperienceRetrieval-augmented generation, agentic workflows, tool use or fine-tuning in production settings.Experience with LLM APIs, orchestration frameworks, vector search, embeddings, retrieval pipelines, evaluation datasets ...

equivalentsPrompt engineering, context design and agentic workflow frameworksEvaluation harnesses, evaluation datasets and automated test suites for AI outputsRetrieval-augmented generation (RAG), vector search, embeddings and retrieval pipelines (desirable)LLM orchestration frameworks (LangChain, Semantic Kernel or equivalents – desirable)Technical and Professional ExpertiseStrong software engineering background … GitHub Copilot, Cursor or equivalents, with a practical view of where they help and where they mislead.Preferred Qualifications and ExperienceRetrieval-augmented generation, agentic workflows, tool use or fine-tuning in production settings.Experience with LLM APIs, orchestration frameworks, vector search, embeddings, retrieval pipelines, evaluation datasets ...

subject-matter experts and hold evidence-based recommendations in front of senior leaders. Familiarity with advanced AI concepts (Desirable): Experience with RAG (Retrieval-Augmented Generation) systems, golden datasets, scoring, regression testing, or A/B experiment design. Domain Exposure (Desirable): Prior experience ...

working in Linux-based environments and proficient in managing containerized workloads and automated CI/CD pipelines.Advanced RAG: Experience building production-ready Retrieval-Augmented Generation systems, including vector database management and semantic search optimization.Preferred QualificationsExperience in the insurance or financial services sector.Deep knowledge ...

Linux-based environments and proficient in managing containerized workloads and automated CI/CD pipelines. Advanced RAG: Experience building production-ready Retrieval-Augmented Generation systems, including vector database management and semantic search optimization. Preferred Qualifications Experience in the insurance or financial services sector. Deep ...

mapping tools. Familiarity with Microsoft 365 cloud ecosystem, Azure integrations, document management systems and virtual data rooms. Exposure to generative AI integration, prompt engineering, RAG architecture and LLM orchestration frameworks. Understanding of security architecture principles and legal‐sector information governance. Legal & Commercial Skills Proven experience in a law firm, ALSP ...

commercial environmentStrong understanding of AI tools and their practical application in business operations, including generative AI, AI agents, prompt engineering, and retrieval-augmented generationA Product Management approach to AI initiatives, covering intake scoring, roadmap prioritisation, outcome measurement, and iterative deliveryConfidence learning and evaluating new AI platforms ...