23 of 23 Remote/Hybrid Retrieval-Augmented Generation Jobs in the South East

engineers who have built AI solutions around document intelligence, enterprise search, knowledge management, NLP or Retrieval-Augmented Generation (RAG), rather than purely research-focused AI. Key Responsibilities Design, build and deploy production-ready LLM and Machine Learning solutions using Azure Databricks, Azure Machine Learning … Foundry Good understanding of MLOps and LLMOps Excellent Python engineering skills with experience using frameworks such as LangChain, LangGraph, PyTorch and Pydantic Experience with RAG, vector search, embeddings, prompt engineering and enterprise retrieval architectures Experience building AI solutions within document-heavy environments such as legal, financial services, insurance ...

enterprise environment. Driving build versus buy evaluations and recommending appropriate technologies. Delivering solutions including retrieval-augmented generation (RAG), agentic AI, automation, and intelligent decision-support tools. Working closely with engineering, security, governance, and business stakeholders. Navigating complex and ambiguous problem spaces to identify practical … fundamentals and experience building scalable applications. Experience making architecture and technology decisions within enterprise organisations. Strong knowledge of modern AI engineering practices, including LLMs, RAG, agentic workflows, and MLOps concepts. Experience working with cloud platforms, ideally AWS. Ability to balance innovation with risk, governance, and operational requirements. Strong stakeholder management ...

solution approaches across the modern AI stack, including Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), Vector Databases and MLOps. Support clients in navigating cloud, security, data governance and operating model considerations required for enterprise AI adoption. Communicate complex machine learning ...

modern AI technologies and concepts, including: Generative AI Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Vector Databases AI Solution Architecture MLOps Principles AI Governance and Risk Considerations Candidates are not expected to be hands-on developers but should be capable ...

responsible for: Designing and developing AI agents using modern LLM frameworks Building Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge sources Developing and deploying Machine Learning models for intelligent decision-making Integrating AI services with enterprise APIs and data platforms Engineering prompts, tool calling ...

understanding of the modern AI ecosystem, including: Generative AI Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Vector Databases MLOps Experience leading the implementation of enterprise-scale AI solutions and being accountable for delivery outcomes. Knowledge of cloud platforms such ...

understanding of the modern AI ecosystem, including: Generative AI Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Vector Databases MLOps Experience leading the implementation of enterprise-scale AI solutions and being accountable for delivery outcomes. Knowledge of cloud platforms such ...

Apply advanced techniques including optimisation, forecasting, statistical modelling and AI Develop LLM-based solutions, including: Retrieval-Augmented Generation (RAG) Fine-tuning and prompt engineering Agent-based workflows Work with large and complex datasets, both structured and unstructured Write clean, scalable Python code for model … Pandas, NumPy, SciPy or similar) Solid grounding in statistics, probability and data analysis AI & LLM Experience Hands-on experience with large language models, including: RAG pipelines Fine-tuning approaches Agent-based architectures A practical understanding of how to apply LLMs to real-world use cases Tools & Engineering Experience with model ...

agentic workflow frameworks Evaluation harnesses, evaluation datasets and automated test suites for AI outputs Retrieval-augmented generation (RAG), vector search, embeddings and retrieval pipelines (desirable) LLM orchestration frameworks (LangChain, Semantic Kernel or equivalents – desirable) Technical and Professional Expertise Strong software engineering background ...

practices within engineering teams Drive improvements in automation frameworks and testing tools Provide expert oversight on AI model validation, including Generative AI and RAG solutions Identify risks early and implement mitigation strategies Mentor and coach engineers to build strong testing capability across teams Key Responsibilities Define and deliver testing strategies … platforms) Proficiency in one or more: Python, Java, JavaScript, SQL, or R Proven experience in: AI/Generative AI testing RAG (Retrieval-Augmented Generation) solution validation (e.g. RAGAS framework) CI/CD, DevOps, and cloud-based test integration Ability to define and implement ...

/CD pipelines (Azure DevOps). * Demonstrated hands-on exposure to at least one of: LLM API integration, vector databases, prompt engineering, or RAG pipeline construction * Familiarity with REST-based AI APIs (OpenAI, Anthropic, Google Vertex AI, or equivalent). * Basic understanding of embeddings, semantic search, and token-based context ...

learning solutions Practical experience with Large Language Models (LLMs), Generative AI and prompt engineering Knowledge of modern AI tooling and frameworks, including exposure to RAG architectures and vector databases Experience working with cloud platforms, ideally Google Cloud Platform (GCP) Strong software engineering fundamentals and experience developing scalable applications Excellent communication ...

Experience with MCP and Vertex/storage-related infrastructure Strong understanding of AI architecture, orchestration, and scalable deployment practices Preferred Experience Building AI agents, RAG pipelines, or enterprise AI applications Working with cloud-based AI/ML platforms and data storage solutions Collaborating with engineering and product teams to deliver ...

bring a strong STEM/computing background. Knowledge and understanding of UK Defence. Experience in one or more of the following technical disciplines: LLMs, RAG,Agentic AI(e.g. LangGraph). Computer Vision. AI for audio and speech. What we offer We offer a combination of mentoring and internal and external ...

solutions). Lead architectural decisions , ensuring responsible AI, explain ability, security, and operational robustness are embedded by design. Evaluate and integrate LLMs, vector databases, RAG patterns, agent-based frameworks, and AI APIs into enterprise-ready solutions. Champion automation across the AI lifecycle from data ingestion to deployment and run. Service … cloud platforms (AWS, Azure or GCP) and modern DevOps practices Experience integrating machine learning/GenAI models into real-world systems Experience with LLMs, RAG, vector search, conversational AI, or unstructured data pipelines Familiarity with AI tooling/frameworks (e.g. LangChain, LlamaIndex, Haystack, Hugging Face, CrewAI) Experience leading SaaS/ ...

Robotics team following continued growth and investment. This is an exciting opportunity to join a multidisciplinary engineering team developing next-generation intelligent systems that combine AI, machine learning and robotics to solve complex real-world challenges. Working closely with software engineers, data scientists and product teams … modern software architecture. Experience working within Agile development environments. Excellent communication and stakeholder engagement skills. Desirable Experience with ROS/ROS2. Experience with LLMs, RAG or Agentic AI architectures. Knowledge of reinforcement learning or motion planning. Familiarity with Docker, Kubernetes and CI/CD. MSc or PhD in Computer Science ...

deployment Build robust evaluation harnesses—offline metrics, online experiments, guardrails and monitoring Apply LLMs and generative AI techniques where they're the right tool—RAG, fine-tuning, prompt engineering, agentic patterns Monitor models in production for drift, degradation, bias and safety concerns Partner with data engineering peers to build … experience—deploying, serving and monitoring models at scale LLM and generative AI tooling exposure (LangChain, LlamaIndex, vector databases such as Pinecone, Weaviate or pgvector, RAG patterns, fine-tuning workflows) MLOps platforms (MLflow, Kubeflow, Vertex AI, SageMaker, Databricks or equivalent) Cloud experience (AWS, GCP, Azure), containerisation and basic data engineering/ ...

service platforms that allow teams to rapidly integrate AI into coding, testing, deployment, monitoring and operations. You'll establish best practices for prompt engineering, RAG architectures, agentic workflows, model versioning, experimentation and governance, ensuring AI capabilities are scalable, secure and production ready. Beyond the technology, you'll play a pivotal … delivering large-scale, developer facing platforms and leading complex technical initiatives You have hands-on experience building AI-enabled applications using LLMs, agentic frameworks, RAG, prompt engineering and modern GenAI tooling You have a strong knowledge of software engineering fundamentals, including system design, APIs, CI/CD, testing, observability, cloud ...

working in regulated environments or with legal workflows. Thorough understanding of AI technologies used in legal environments (LLMs, NLP, extraction/classification models, summarisation, RAG pipelines, etc.) Hybrid Working Birketts is a flexible business which has embraced a hybrid working model where our colleagues enjoy a mix of home ...

consultative environment. Responsibilities Design end-to-end AI and Generative AI architectures for enterprise-scale transformation programmes Define solution architectures leveraging LLMs, RAG, vector databases and AI agent frameworks Work with senior client stakeholders to translate business challenges into scalable AI solutions and implementation roadmaps Design secure, responsible and scalable … experience designing and delivering enterprise AI, Machine Learning or Advanced Analytics solutions Strong understanding of modern AI technologies including Generative AI, LLMs, Prompt Engineering, RAG and Vector Databases Experience architecting production-grade AI platforms and applications Strong knowledge of at least one major cloud platform (Azure, AWS or GCP) Ability ...

reusable agent components and playbooks • Proactively surface new automation opportunities across the business Key Skills • Python & LLM agent frameworks (LangChain, CrewAI, LlamaIndex) • Prompt engineering & RAG pipelines • Business analysis & stakeholder management • Process mapping & workshop facilitation • Microsoft 365 & Microsoft Copilot No-code/low-code tooling (Zapier, Make) Desirable Skills • Experience … etc. • Strong enough technically to assess feasibility and scope what is buildable; commercially sharp enough to prioritise what is worth building. • Familiarity with LLMs, RAG pipelines, tool/function calling, and integrating AI into real business workflows. • Proven ability to lead discovery workshops and translate complex business problems into clear ...

solution concepts into actionable architecture, design and delivery guidance for engineering teams. Design and implement AI-powered assistants, agents and intelligent workflow solutions leveraging RAG and advanced orchestration techniques. Evaluate emerging AI technologies, frameworks and industry trends to drive innovation and best practice. Provide technical leadership, mentoring and guidance … strongly preferred (e.g., Bedrock, Lambda, Step Functions and related AI services). Hands-on experience implementing AI agents, multi-agent systems, intelligent workflow automation, RAG architectures and AI-powered assistants in enterprise environments. Strong knowledge of agentic frameworks and orchestration technologies such as LangGraph, AutoGen, CrewAI, Agent Development ...

platforms built on AWS. Working closely with senior stakeholders, product teams and engineering leads, you'll design and implement AI agents, multi-agent systems, RAG architectures and intelligent workflow solutions leveraging AWS services including Bedrock, Lambda and Step Functions. You'll be responsible for defining architecture standards, shaping technical strategy … remaining hands-on with the latest AI technologies. SC Clearance OR eligibility is madatory. Key Skills: AWS Bedrock, Agentic AI, Generative AI, AI Agents, RAG, LangGraph, CrewAI, AutoGen, ADK, Solution Architecture, AWS Lambda, Step Functions, Insurance, Enterprise Architecture, AI Strategy. ...