451 to 475 of 836 Retrieval-Augmented Generation Jobs in the UK

include Docker, Kubernetes, Azure, Infrastructure as Code, enterprise APIs, identity and access management, observability and modern DevOps practices. Exposure to AI platforms, LLM integration, RAG, agent frameworks or accelerated compute would be valuable, but we are primarily looking for strong architectural breadth and the ability to deliver complex technology ...

launch and architecting AI systems on cloud platforms (e.g., GCP). Experience building pipelines for structured and unstructured data using both vector databases and RAG‐like architectures to power enterprise AI solutions. Experience leading technical discovery sessions with customers. Active, or the ability to obtain, a Security Check ...

automation, and codified engineering practices. What You Will DoDesign and build scalable platform capabilities across Azure to support AI use cases (Agents, Agentic workflows, RAG, LLMs), including APIs, integrations, and model serving layers. Produce high-quality technical designs and guide implementation, ensuring solutions are secure, maintainable, and aligned to architectural ...

Qualifications Engineering experience with cloud-native systems (APIs, microservices, containerization, serverless). Deep expertise in 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 ...

Hubspot. About the teamThe AI Engineering team builds the systems and capabilities behind Typeform's products. We use machine learning, large language models, RAG, and agentic systems to help customers collect, understand, and act on information in more conversational and personalised ways. The team owns the journey from experimentation through … Engineer at Typeform, you will design, build, and operate the systems behind our AI products. Your work will span generative AI applications, enterprise RAG systems, agentic workflows, model evaluation, machine learning pipelines, and the infrastructure required to run them reliably at scale. This is a hands on engineering role with ...

only custom-building where neither can deliver the required outcome. Support AI-enabled use cases across areas such as board reporting and narrative generation, management reporting summaries, finance process automation, forecasting and planning support, document ingestion and extraction, reconciliation and workflow automation, insight generation from structured … Have: Significant experience in applied AI, machine learning, data science, analytics engineering, automation or AI-enabled transformation. Strong understanding of generative AI, LLMs, RAG, agents, workflow automation, prompt engineering, evaluation and AI solution design. Familiarity with platforms such as Azure OpenAI, Microsoft Fabric, AWS Bedrock, GCP Vertex AI, Snowflake Cortex ...

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 ...

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 ...

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 ...

audit-ready evidence generation. AI Enablement Implement AI/ML components within the model workflow, including LLM-based automation for model documentation generation and updating, intelligent data quality checks, and workflow assistance. Integrate AI tooling into a controlled, auditable, production-grade environment, with appropriate testing, monitoring, and governance … Solid AI/ML knowledge, including practical experience with machine learning libraries and/or LLM-based application development (e.g., API integration, prompt engineering, RAG-style document workflows). Strong experience with test automation, CI/CD, and modern software engineering practices (Git, code review, containerization). Experience working with ...

drive progress without being pushed Consulting or client-facing delivery experience is a strong advantage Exposure to GenAI applications in decisioning — personalised content generation, AI-driven offer selection Preferred Experience evaluating purpose-built decisioning solutions and contributing to capex/opex business cases Familiarity with real-time streaming … Technical Skills Advanced 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 management Agentic AI frameworks — LangChain, LangGraph, AutoGen, or similar; building multi-step autonomous workflows Machine Learning — model development, training, evaluation, and deployment ...

drive progress without being pushed Consulting or client-facing delivery experience is a strong advantage Exposure to GenAI applications in decisioning — personalised content generation, AI-driven offer selection Preferred Experience evaluating purpose-built decisioning solutions and contributing to capex/opex business cases Familiarity with real-time streaming … Technical Skills Advanced 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 management Agentic AI frameworks — LangChain, LangGraph, AutoGen, or similar; building multi-step autonomous workflows Machine Learning — model development, training, evaluation, and deployment ...

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 ...