1 to 25 of 32 Contract Retrieval-Augmented Generation Jobs in the UK

Experience with: AWS: boto3, Bedrock, SageMaker, Lambda, S3, EC2 Azure: Azure OpenAI Service, Cosmos DB Retrieval-Augmented Generation (RAG), Graph RAG Embedding models and LLM training fundamentals Damia Group Limited acts as an employment agency for permanent recruitment and employment business for the supply ...

LlamaIndex for building LLM-powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise data MLOps & Infrastructure MLOps: Model versioning, monitoring, logging Bias Detection & Mitigation Content Filtering & Moderation Explainability & Transparency ...

business requirements into technical architectures for GenAI and machine learning use cases. Implement prompt engineering, retrieval-augmented generation (RAG), and integration patterns with enterprise systems. Configure and optimise Microsoft Copilot Studio and other AI tools for internal use cases. Support the development of repeatable … Azure AI services. Strong ability to quickly prototype and test AI/ML solutions. Experience with APIs, vector databases, and integration patterns. Understanding of RAG, LLMOps, and prompt engineering. Job Offer Competitive daily rate (Inside IR35). Opportunity to work on innovative AI projects in the financial services industry. Temporary ...

. Multi-Agent Ecosystems: Design architectures that support Agent-to-Agent (A2A) communication, orchestration, and collaboration across diverse business functions. LLM Strategy & RAG: Define model selection, fine-tuning strategies, and build Retrieval-Augmented Generation (RAG) pipelines to ensure contextual accuracy and reduced hallucinations. Context ...

application developers to translate business objectives into high-quality AI outcomes. A working understanding of Retrieval-Augmented Generation (RAG) is essential to ground model responses in authoritative enterprise content and to reduce hallucinations. This role blends hands-on engineering with rigorous experimentation, evaluation … . Utilize and manage RESTful APIs/SDKs to integrate model calls within web services, back-end jobs, and enterprise applications. Design and implement RAG pipelines (chunking, embeddings, indexing, ranking/citation policies) to ground responses in approved content stores. Establish offline/online evaluation frameworks (accuracy, safety, faithfulness, latency ...

subject matter expert, you will mentor a high-performing team, manage cross-functional integrations, and stay at the bleeding edge of AI (RAG, MCP, and SageMaker) to keep our projects ahead of the curve. What You'll Do Architect Decision Systems: Design innovative AI/ML models that … Science & Machine Learning. Cloud Expertise: Intermediate+ proficiency in Amazon SageMaker . Modern AI: Familiarity with Retrieval-Augmented Generation (RAG) and Model Context Protocol (MCP) . Engineering Rigor: Solid understanding of the Software Development Life Cycle (SDLC) . Please let me know if you would ...

Engineer will be responsible for developing secure, scalable, and high-performing AI solutions, including document intelligence workflows, generative AI applications, and retrieval-augmented systems. This includes working on model orchestration, prompt engineering, document extraction pipelines, and system integrations with enterprise platforms such … intelligent document processing pipelines using Azure AI Doc Intelligence for tasks such as classification, extraction, OCR, and automated document workflows. Implement RAG (Retrieval-Augmented Generation) architectures using Azure Search or vector databases. Integrate AI capabilities with enterprise systems through REST APIs, Azure Functions, Logic ...

Communicate complex concepts to all stakeholders. At least 3 years of experience in AI solution engineering. Large Language Models experience including prompt engineering and RAG implementations. Expert data analytics, MLOps practices and API development. Desirable knowledge in Docker and Kubernetes ...

least 2 AI domains: NLP, NLG, Computer Vision, Machine Learning, GenAI etc. Hands-on experience with fine-tuning/training LLMs and complex Graph RAG solutions (production environment). Technical Skills: Extensive knowledge of cloud services and tools (Azure & Databricks preferred), ), including Azure Machine Learning, Vertex AI, AI Search, Databricks ...

experience and API development Experience with data pipelines and vector databases Knowledge of SRE, DevOps, and platform engineering practices Exposure to AI systems, LLMs, RAG, or agent architectures Experience working with UK government or secure environments You'll work alongside expert architects and engineers to deliver complex, high-impact solutions ...

month rolling contract, paying up to £1000 per day, depending on experience. Experience and skills required for the Data Scientist, Advanced SQL, LLM, RAG, Machine Learning, Python, Java Development experience in one or more object-oriented programming languages (e click apply for full job details ...

track record delivering enterprise-scale AI/ML and intelligent automation Strong hands-on knowledge of cloud AI platforms, data engineering and LLM/RAG architectures Experience implementing MLOps, observability and model governance Commercially minded, able to link AI outcomes to revenue, efficiency and customer impact Background within consumer ...

observability). Demonstrated success in leading teams Deep understanding of AI/ML solutions implementation, with emphasis on LLM applications and retrieval-augmented generation. Expertise in modern SDLC and DevOps: CI/CD (e.g., Jenkins/GitLab), infrastructure as code (e.g., Terraform/CloudFormation), automated testing ...

artificial intelligence, and machine learning, with considerable in-depth knowledge in implementing solutions using AWS. Practical cloud-native experience, specifically with AWS. Experience with RAG-based semantic search and LLM inference workflows using OpenAI and Claude models. ...

Foundry , Azure OpenAI , and Azure AI Document Intelligence for enterprise use cases (IDP, GenAI copilots, knowledge retrieval). Establish standards for RAG architectures (vectorization, indexing, chunking, grounding, citation policies) using Azure Search or vector-enabled data stores click apply for full job details ...

/Kent preferred Day Rate: £300–£325 per day Key Requirements: Hands-on exposure to Azure AI and Machine Learning Experience with Agentic AI , RAG systems , and GraphRAG At least 10+ years’ experience in .NET Please note: This role cannot offer sponsorship. Applicants must have full rights to live ...

TypeScript-based applications Understanding of semantic/graph data (e.g., RDF triples, SPARQL , Amazon Neptune ) Ability to validate AI-supported features, including LLM/RAG behaviours via Amazon Bedrock Knowledge of performance testing for serverless architectures and WCAG 2.2 AA accessibility Familiarity with GDS Standards and testing in the public ...

solutions spanning data preparation, modelling, APIs, and production integration* Build and optimise ML and LLM-driven services, including prediction models, personalisation, and retrieval-augmented systems* Collaborate with business stakeholders to frame problems, define success metrics, and deliver measurable outcomes* Develop services, APIs, and integrations that embed … solutions into production environments* Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn* Experience working with LLMs, including prompt design, RAG, or fine-tuning* Experience building APIs and integrating AI systems into real products* Solid understanding of data pipelines, feature engineering, and model evaluation* Experience working ...

office The Role AWS Solution Designer (with GenAI experience) Your responsibilities: Lead end to end GenAI initiatives including model creation, finetuning, benchmarking, evaluation, and RAG system design click apply for full job details ...

translate business outcomes into actionable AI roadmaps and solution designs. You will also guide implementation teams on best practices for prompt engineering, grounding strategies, RAG patterns, observability, MLOps, and Responsible AI-ensuring solutions are robust, compliant, and production ready. This role suits a hands on architect who can balance strategic … Foundry, Azure OpenAI, and Azure AI Document Intelligence for enterprise use cases (IDP, GenAI copilots, knowledge retrieval). Establish standards for RAG architectures (vectorization, indexing, chunking, grounding, citation policies) using Azure Search or vector enabled data stores. Create architectural decision records (ADRs), guardrails, and reusable blueprints for solution ...

Agentic AI solutions aligned to real business workflows Build and orchestrate autonomous agents with planning, reasoning, and tool use Develop LLM-driven systems including RAG, Q&A, and enterprise copilots Integrate GenAI into existing platforms, products, and processes Own delivery end-to-end: design through to production Work closely with … Generative AI and LLMs Agentic AI frameworks such as LangGraph, AutoGen, or CrewAI Python with modern AI libraries (LangChain, Hugging Face, PyTorch) Experience building RAG pipelines and knowledge retrieval systems Cloud platforms: Azure, AWS, or GCP Microsoft/Azure (Highly Desirable) Microsoft AI Foundry Azure AI Agent Service ...

Foundry , Azure OpenAI , and Azure AI Document Intelligence for enterprise use cases (IDP, GenAI copilots, knowledge retrieval). Establish standards for RAG architectures (vectorization, indexing, chunking, grounding, citation policies) using Azure Search or vector-enabled data stores. Create architectural decision records (ADRs), guardrails, and reusable blueprints for solution … Analytics, Synapse Analytics, Azure DevOps . You should have hands-on experience in Deep knowledge of LLMs (prompting, system prompts, grounding, evaluation), embeddings , and RAG design (index selection, chunking strategies, reranking, citations). Strong design of secure API and event-driven integration patterns; familiarity with microservices and domain-driven design ...

that enhance global sales workflows. Build scalable backend services and full-stack applications for internal teams. Architect, implement, and optimize LLM orchestration frameworks and RAG-based solutions. Collaborate with cross-functional teams to define requirements and deliver innovative tools. Ensure reliability, scalability, and performance of distributed systems handling massive datasets. … workflows . Strong proficiency in Angular (primary frontend); React optional. Hands-on experience with LangChain, LangGraph, and Indexify , with a deep understanding of RAG architectures . Expert-level SQL and experience with BigQuery and vector databases (Pinecone, Weaviate, Vertex AI Search). Proven track record in MLOps and deploying ...

that enhance global sales workflows. Build scalable backend services and full-stack applications for internal teams. Architect, implement, and optimize LLM orchestration frameworks and RAG-based solutions. Collaborate with cross-functional teams to define requirements and deliver innovative tools. Ensure reliability, scalability, and performance of distributed systems handling massive datasets. … workflows . Strong proficiency in Angular (primary frontend); React optional. Hands-on experience with LangChain, LangGraph, and Indexify , with a deep understanding of RAG architectures . Expert-level SQL and experience with BigQuery and vector databases (Pinecone, Weaviate, Vertex AI Search). Proven track record in MLOps and deploying ...

months IR35: Outside Location: London (onsite once per month ) Start: ASAP What you’ll work on Building Agentic AI workflows and automation Designing RAG pipelines for insurance data Developing LLM-powered tools using Python , LangChain , LlamaIndex , and vector databases Evaluating, fine-tuning, and integrating LLMs (OpenAI/Anthropic/Mistral … Data Science & Engineering teams to productionise models What you’ll need Strong Data Science + AI Engineering background Hands-on experience with Agentic AI , RAG , LLMs , LangChain , Python Knowledge of vector search, embeddings, and scalable pipelines Experience working in enterprise or regulated environments Must have insurance domain experience Insurance domain ...