51 to 69 of 69 Retrieval-Augmented Generation Jobs in the North West

transformation programme. You will design and build scalable data pipelines in GCP, develop cloud-native solutions, and support AI/LLM and RAG initiatives across a large-scale environment. You will work on event-driven architectures with Kafka, write robust Python and SQL, and help ensure data quality, governance ...

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 ...

applications in production environments. Experience with vision‐language models or multimodal AI over images, video, inspection evidence, diagrams, screenshots, or technical records. Experience with RAG over structured and unstructured data. Familiarity with observability, log analysis, incident response, support tooling, runbooks, or developer tools. Experience building workflow UIs where AI assists ...

develop new skills and hone existing ones. We work for a huge variety of interesting, international, and world-leading clients on exciting next generation technology-enabled projects. We are looking for candidates with AI/GenAI Architect based expertise to join us, working in fast-paced teams with … content around data design, architecture and engineering like collateral and playbooks on KX, improving our artefacts and strategies.Knowledge of generative AI architectural patterns including RAG & fine tuning.Experience training & deploying machine learning models using a range of techniques (e.g. Classification, Regression, Neural Networks, etc).Experience with developing and deploying applications ...

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 ...

Hugging Face), advanced GenAI frameworks (LangChain, HF Transformers, LlamaIndex) & Agentic architectures (LangGraph, SmolAgents, PydanticAI) Prompt Engineering: Deep prompt engineering & optimization skills for GenAI.Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented GenAI (RAG) for knowledge applications.GenAI ModelOps/MLOps & Governance: GenAI ModelOps/MLOps knowledge … with ethical AI governance focus.Multimodal & Code Generation: Architected GenAI for multimodal (vision, audio, language) & code generation.ER&I GenAI Applications: Applied GenAI to ER&I use cases to create business value.Enterprise Software Integration: Designed GenAI integrations with SaaS/ERP for business process automation.GenAI Impact Reporting: Designed advanced reporting ...

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 ...

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 ...

including API design, automated testing, asynchronous processing, dependency management and production debugging. Practical experience with agent orchestration, structured tool calling, workflow state, retrieval-augmented generation and human-in-the-loop patterns. Experience building secure integrations with enterprise APIs, repositories, cloud services, CI/ ...

date with the rapidly evolving technology landscape.Responsibilities:Develop and integrate AI-powered applications using modern Microsoft and Azure technologies Build and improve RAG-based solutions, intelligent search and knowledge servicesExplore and develop AI agents capable of completing tasks and automating business processesCreate prototypes and proof of concepts to assess … machine learning or generative AI technologiesExperience working with Azure and cloud-based technologiesKnowledge of technologies such as Azure OpenAI, Microsoft Foundry, Semantic Kernel, RAG or vector databasesUnderstanding of AI agents, LLMs and modern AI development approachesStrong software engineering fundamentals, including source control, testing and CI/CDGenuine interest ...

platform that underpins our clinets conversational assistant and wider AI initiatives. You will take responsibility for the runtime, infrastructure, and operational foundations underpinning our RAG pipelines, LLM orchestration, and vector search, built across Microsoft Azure and Microsoft Foundry. Where prototypes and proof-of-concepts exist, you will … Build and extend a scalable AI platform via Microsoft Foundry. Own and optimise Foundry solutions for accuracy, scale, and latency. Harden the production RAG pipeline, covering inference, retrieval, and ingestion. Architect Azure services using Terraform infrastructure-as-code. Scale vector database and embedding pipelines. Build ...

STEM field. Strong leader, able to communicate clearly at all levels. Track record deploying business critical ML models in production. Experience building and scaling RAG applications with semantic search and text embeddings. Cloud computing experience, ideally Azure, AWS, or GCP. Strong ML and data science fundamentals, including NLP. Ability … manage AI/RAG/GenAI risk and fine-tune models on proprietary datasets. Strong Python and SQL skills, with frameworks such as PyTorch and TensorFlow. If you're ready to shape AI strategy from the ground up and see it through to production, at real scale, this ...

concept through to production deployment Designing and developing AI and Machine Learning solutions using Azure and modern AI technologies Building production-ready LLM applications, RAG pipelines and AI agents Working closely with Data Engineering teams to prepare and integrate structured and unstructured data Collaborating with Infrastructure teams to deploy secure … Science and Machine Learning Experience designing and deploying production AI solutions Strong knowledge of AI, Machine Learning and Large Language Models (LLMs) Experience developing RAG solutions and AI agents Excellent Python skills alongside modern AI/ML frameworks and SDKs Experience with Azure AI services or another enterprise AI cloud ...

Neo4j/Knowledge Graph experience Experience with Vector Databases, Search or Indexing Strong understanding of data modelling and governance Experience supporting AI, LLM or RAG use cases Nice to have: Enterprise Knowledge Management/Knowledge Base experience Semantic Search Large-scale Search platforms AI/LLM and RAG experience Financial ...

Searchability seeks an experienced AI Engineer to join a major enterprise AI transformation programme, focusing on AI Agents, RAG and GenAI. You’ll design and build agentic AI solutions, and develop APIs in a complex enterprise environment. The role involves working with large language models, prompt engineering, and production-grade ...

team of engineers. Key Responsibilities * Lead the development and deployment of AI-powered tools to improve efficiency and productivity * Design advanced solutions including automation, RAG, and LLM-based workflows * Collaborate with stakeholders to identify and deliver strategic AI initiatives that deliver measurable business value * Provide guidance on AI architecture, tooling … with AI engineering, or software engineering (e.g. Python, Java, JavaScript/TypeScript etc.) with libraries/frameworks such as PyTorch, TensorFlow etc.) * Experience with RAG and LLM-based solutions * Solid understanding of AI architectures and data pipelines * Knowledge of security, compliance, and governance principles from a development perspective * Proven mentoring ...

attention to detail. Ability to work effectively within Agile squads and cross-functional environments. Desirable: Exposure to AI testing methods (e.g., validating LLM outputs, RAG consistency, AI behaviour evaluation). Experience using AI-powered QA tools or test-generation frameworks. Knowledge of cloud environments (AWS/Azure ...

pitches and proposals. Technical Delivery & Innovation Familiarity and experience with AI concepts and techniques, such as large language models, machine learning, or Retrieval-Augmented Generation models. Experience or desire to grow capability in using AI to support insight workflow optimisation or automation, looking ...