51 to 75 of 279 Retrieval-Augmented Generation Jobs in England

Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 – AI Specialised Customer Service Chatbot Project Combine prompt … engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning ...

with the team to develop GenAI proof-of-concepts (POCs) for clients using technologies like Retrieval-Augmented Generation (RAG) and intelligent agents. Scale existing POCs to production-ready solutions for customer use. Design and develop Full Stack applications for both GenAI and non-GenAI ...

emerging AI/ML capabilities within modern data platforms. Exposure to vector databases, embeddings, retrieval-augmented generation (RAG), and AI-ready data architectures. Retail, wholesale, supply chain, or large-scale transactional data experience. ...

hands-on with Python and Azure , possessing a proven track record of designing and deploying Retrieval-Augmented Generation (RAG) patterns. Key Responsibilities Architect & Govern: Design and implement robust on-premises, cloud, and hybrid AI solutions, ensuring strict technical governance and best practices across … client relationships to secure consensus on complex technical architectures. Essential Skills Clearance: Active UK Government Security Check (SC). GenAI: Expertise in LLMs and RAG architectures. Python: Strong proficiency alongside PySpark for data engineering. Azure: Deep familiarity with native tools (AI Search, Document Intelligence). MLOps: Understanding of LLMOps frameworks ...

hands-on with Python and Azure , possessing a proven track record of designing and deploying Retrieval-Augmented Generation (RAG) patterns. Key Responsibilities Architect & Govern: Design and implement robust on-premises, cloud, and hybrid AI solutions, ensuring strict technical governance and best practices across … client relationships to secure consensus on complex technical architectures. Essential Skills Clearance: Active UK Government Security Check (SC). GenAI: Expertise in LLMs and RAG architectures. Python: Strong proficiency alongside PySpark for data engineering. Azure: Deep familiarity with native tools (AI Search, Document Intelligence). MLOps: Understanding of LLMOps frameworks ...

intersection of DevOps, cloud infrastructure and applied AI owning the full lifecycle of Retrieval-Augmented Generation (RAG) and LLM-powered systems across modern cloud architecture. This role is about engineering, not research. You will architect and run the infrastructure that enables AI to perform … hardened, production-ready services while shaping a reusable AI platform capable of supporting multiple products. What You'll Be Doing Design and optimise scalable RAG pipelines and vector search systems Orchestrate multi-model AI services with a focus on latency, resilience and performance Productionise GenAI workflows and ensure they operate ...

managing multi-API workflows using tools like LiteLLM to ensure flexibility and resilience. Building sophisticated Retrieval-Augmented Generation (RAG) systems, leveraging advanced techniques like embeddings with Voyage AI, rerankers , and query enrichment . Designing and maintaining efficient data pipelines and vector storage solutions using … PyTorch. Proven experience building and deploying applications with LLM APIs such as OpenAI , Anthropic , Gemini , and DeepSeek . Hands-on experience with the full RAG pipeline, including vector embeddings , rerankers , and data indexing in databases like MongoDB. Practical knowledge of LLM fine-tuning, prompt engineering, and performance optimization. Familiarity with ...

data scientists, software engineers, and business stakeholders. LLM & Agent Development: Build autonomous AI agents, implement Retrieval-Augmented Generation (RAG) pipelines, and fine-tune LLMs using PEFT techniques like LoRA. Data Engineering: Design and maintain robust ETL/ELT pipelines to process structured and unstructured ...

drive enterprise opportunities from qualification to close. Develop and maintain a strong perspective on how AI – including large language models, agentic architectures, and RAG-based solutions – can drive measurable business value across verticals and functions. Understand customer pain points in adopting and implementing AI solutions, and position Uniphore … trusted partner to address them. Deliver compelling technical presentations and demos showcasing GenAI, Agentic AI, RAG, and LLM-based capabilities tailored to each prospect’s context. Build and deliver custom demos and proof-of-concepts (POCs) to validate business value and technical feasibility. Conduct discovery sessions with key business ...

Responsibilities Design & Deliver: Architect and implement cloud and AI-ready solutions on Azure, building repeatable patterns and integration services that support next-generation workloads. Secure AI Architecture: Develop and scale secure infrastructure architectures that allow applications to safely access both cloud-based backend services and on-premises data … Beyond the Basics): Real-world enterprise experience designing and deploying solutions centred around agentic workflows, Retrieval-Augmented Generation (RAG), and vectorisation patterns, rather than purely self-taught or personal interest projects. Software Engineering & Tech Stack: High proficiency in Python and PowerShell for building automation ...

/GAI technologies and large language models (LLMs) Advanced AI Integration : Apply experience with retrieval-augmented generation (RAG), vector databases (e.g. Pinecone, Weaviate, FAISS), and enterprise search for AI-driven knowledge discovery Optimize AI Performance : Utilize practical experience designing structured prompts, fine-tuning models ...

architectures on AWS, accelerating delivery of conversational AI products using Amazon Bedrock, agentic frameworks, and retrieval-augmented generation (RAG) patterns. Key responsibilities: Own the target-state architecture for GenAI products (voice and chat), including multi-account strategy, landing zone alignment, network patterns, and environment … segregation (dev/test/prod). Define reference architectures for Amazon Bedrock, model orchestration, RAG, tool/function calling, and agentic workflows (e.g., LangChain/LangGraph/CrewAI/Strands-style patterns) with clear guardrails. Design enterprise-grade knowledge architectures: ingestion pipelines, chunking strategies, embedding/model choices, vector ...

unlock value Building solutions using Large Language Models (LLMs), Agentic/autonomous AI workflows, Retrieval-Augmented Generation (RAG), Modern AI tooling (e.g. LangChain, vector databases, APIs) Rapidly prototyping and iterating on solutions within fast-paced timelines Translating complex technical concepts into practical, commercial outcomes … Looking For Strong software engineering fundamentals (Python, APIs, version control, testing) Experience working with modern AI technologies, such as LLMs/Generative AI, RAG pipelines, Agent-based architectures Ability to work in fast-paced, ambiguous environments and deliver tangible outcomes quickly Strong communication skills and comfort working in client-facing ...

Integrate AI/ML components into applications and operational workflows Design and implement Retrieval-Augmented Generation (RAG) solutions Evaluate LLM performance, identify failure modes, and implement mitigation strategies Test, debug, and improve non-deterministic AI systems Balance AI approaches with deterministic or statistical methods … performance Ability to debug complex, non-deterministic behaviours Strong communication skills to explain AI trade-offs and risks Bonus Skills Hands-on experience with RAG architectures and LLM tooling Experience working in regulated or high-assurance environments Familiarity with AI safety, risk, and governance considerations Background in software engineering (Python ...

Senior AI Engineer - AI Agents - High Profile AI Scale Up - (relocation to Dubai, UAE) Our client is building a next-generation digital platform, one that is deeply ethical, powered by thoughtful design, and built from first principles around AI. Their mission is to create a proactive, intelligent system … Build and maintain LLM agents and agentic workflows end-to-end Design retrieval-augmented generation (RAG) pipelines and grounding strategies Develop multi-step planning, tool use, and execution flows Implement approaches to reduce hallucinations and unsafe model behaviour Partner with product, backend ...

Iterate on model accuracy and retrieval performance using systematic evaluation frameworks (e.g., RAGAS, DeepEval). Build out our AI experiences — things like RAG pipelines , multimodal user experiences , and LLM-powered experiences that actually work in production. Embed Ignitus into the flow of work with low-complexity integrations Experiment … focus on building high-performance AI backends. Experience working with LLMs , vector databases , and retrieval-augmented generation (RAG). Strong understanding of embedding models, rerankers, and hybrid search. Hands-on experience deploying AI systems in production. Experience in dealing with IT audits with prospects. ...

agents for function classification, malware family identification, behavioral summarization, and IOC extraction. Create scalable pipelines for static and dynamic analysis, YARA generation Integrate AI models with binary analysis frameworks and disassemblers Fine-tune or evaluate models for reverse engineering and malware analysis tasks Build tooling for unpacking, emulation … cybersecurity or reverse engineering workflows Experience with AssemblyLine, ANGR, Capstone, QEMU, or Frida Familiarity with retrieval-augmented generation (RAG), embeddings, and vector search Knowledge of malware clustering and similarity analysis Experience building autonomous or semi-autonomous security agents Understanding of symbolic execution or program ...

Language Models (LLMs) and understanding of trade-offs between performance, cost, and capability. Understanding of Retrieval-Augmented Generation (RAG), agent orchestration, prompt engineering, and tool calling. Familiarity with AI standards such as Model Context Protocol (MCP) and Agent2Agent (A2A). Familiar with AI orchestration ...

About the Role We are seeking a Senior Full-Stack Engineer to join our team and help build the next generation of AI solutions. This is a unique opportunity to be a key technical contributor in a fast-paced, innovative environment where you'll wear many hats … trade-offs Experience with prompt engineering techniques — few-shot prompting, chain-of-thought, structured output, and instruction tuning Practical knowledge of RAG (Retrieval-Augmented Generation) architectures, including chunking strategies, vector embeddings, and similarity search Familiarity with LLM orchestration frameworks such as LangChain, LlamaIndex ...

Data Science/Machine Learning Advanced Python skills with ML frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with LLMs, Generative AI, RAG, or Agentic AI solutions Strong SQL and data manipulation experience Experience working with cloud platforms (AWS, Azure, or GCP) Understanding of statistics, predictive modelling, and data ...

advanced frameworks (PyTorch, TensorFlow, Hugging Face, LangChain) Oversee integration of LLMs (OpenAI, Anthropic, Gemini, Mistral) via enterprise platforms (Azure OpenAI, Vertex AI) Implement RAG architectures and manage vector databases (Pinecone, Weaviate, FAISS, Milvus) Data & Engineering Excellence Lead the evolution of modern data platforms (Databricks, Snowflake, Synapse, BigQuery) Ensure robust data ...

connectors and integrations across Microsoft 365, Power Platform, Dynamics, Azure, and third-party APIs. Implement retrieval-augmented generation (RAG) patterns, including knowledge libraries, data sources, grounding, and prompts. Optimize agent behavior through prompt engineering and iterative tuning. Collaborate with business teams to identify automation … building copilot agents Hands-on experience with Microsoft Copilot Studio, Power Platform, or other conversational AI frameworks. Strong understanding of LLMs, prompts, grounding, and RAG workflows. Proficiency with Power Automate, APIs, JSON, Microsoft Graph, and workflow automation. Experience working with Microsoft 365 services (SharePoint, Outlook, Teams, OneDrive). Ability ...

Agentic System Design: Build intelligent AI agents capable of autonomous task execution using LLMs and advanced reasoning frameworks. LLM Specialization: Implement RAG (Retrieval-Augmented Generation) pipelines and fine-tune models using PEFT/LoRA to create domain-specific insurance experts. Production Engineering: Design ...

Agentic System Design: Build intelligent AI agents capable of autonomous task execution using LLMs and advanced reasoning frameworks. LLM Specialization: Implement RAG (Retrieval-Augmented Generation) pipelines and fine-tune models using PEFT/LoRA to create domain-specific insurance experts. Production Engineering: Design ...

Agentic System Design: Build intelligent AI agents capable of autonomous task execution using LLMs and advanced reasoning frameworks. LLM Specialization: Implement RAG (Retrieval-Augmented Generation) pipelines and fine-tune models using PEFT/LoRA to create domain-specific insurance experts. Production Engineering: Design ...