20 of 20 Retrieval-Augmented Generation Jobs in the South East

AI expert ready to take your skills to the next level? Do words like Azure OpenAI, Cognitive Services, prompt engineering, Retrieval-Augmented Generation (RAG) architectures, vector stores, and API integrations make you light up inside? If so, we want to hear from you! At 1st Central , we're on an exciting journey with AI … develop AI and Generative AI solutions using services like Azure OpenAI and Azure Cognitive Services Implement prompt engineering techniques and Retrieval-Augmented Generation (RAG) architectures. Ensure scalability, security, auditability, and efficiency of AI solutions through detailed system design and development practices. Deploy and manage AI solutions via CI/CD pipelines in Azure DevOps … deploying, and managing production-grade AI and Generative AI systems. Extensive experience with Cloud-based AI and Cognitive Services, and Retrieval-Augmented Generation (RAG) architectures. Deep expertise in API integration, preferably within the Azure ecosystem. Experience with Infrastructure as Code (IaC) across development, testing, and production environments. Solid understanding of Azure networking principles, security More ❯

for a Data Scientist with strong NLP and Python skills, and hands-on experience with large language models (LLMs) and Retrieval-Augmented Generation (RAG). You'll be comfortable developing production-ready AI tools and collaborating across engineering, IT, and business functions. About the role: We're hiring a Data Scientist specialising in NLP … internal users across diverse teams - from design and manufacturing to systems engineering - developing tools powered by large language models (LLMs), Retrieval-Augmented Generation (RAG), and modern NLP techniques. From data preparation to algorithm design and deployment, you'll own the full data science lifecycle and help shape the future of AI capability across the … formed GenAI team, with plenty of opportunity to influence tooling, architecture, and strategy. Key Responsibilities: Design and deliver NLP and LLM-based algorithms tailored to internal user needs Apply RAG methods to provide accurate, context-rich AI responses using internal data Work with stakeholders across engineering, manufacturing, and systems teams to translate needs into AI solutions Clean, process, and manage More ❯

problem-solving skills and the ability to work autonomously in a dynamic environment. DESIRABLE SKILLS Experience supporting LLM training or retrieval-augmented generation (RAG). Familiarity with feature stores, vector databases, or embedding pipelines. Understanding of data quality, lineage, and governance best practices. Exposure to cloud platforms (AWS, Azure, or GCP) and distributed compute More ❯

Prompt Engineer (AI & Data) – Junior to ExperiencedRemote work - United Kingdom Competitive day rate AI | LLMs | RAG | Healthcare Tech | Data Engineering Tech for Good | Real-World Impact | Ethical AI We're Hiring: Full Stack Developer for Generative AI ApplicationsAre you a seasoned developer excited about the future of AI? We're looking for a Full Stack Developer with a strong backend … Be Doing Designing, testing, and refining prompts for LLMs (OpenAI, Claude, etc.) Building prompt libraries and evaluation frameworks Structuring unstructured data (PDFs, notes, forms) into usable formats Working with RAG pipelines and vector databases (FAISS, Pinecone, etc.) Embedding LLMs into user-facing healthcare tools (e.g., AI assistants, in-context help) Collaborating with product, design, and clinical teams to ship real … and prompt engineering (OpenAI, Anthropic, etc.) Familiarity with structured (SQL, JSON, CSV) and unstructured data Exposure to vector stores and retrieval-augmented generation (RAG) Strong Python skills and comfort working with APIs and data pipelines Bonus: experience in healthcare, accessibility, multilingual interfaces, or regulated environments Why Join? Work on AI that actually helps people More ❯

cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and presentation skills. Ensure the ethical use More ❯

cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and colleagues, using data visualisation, storytelling, and presentation skills. Ensure the ethical use More ❯

LLM & Generative AI Engineer. Description Work on emerging GenAI projects Design and Develop state of the art language models Develop proof of concepts Explore Retrieval Augmented Generation (RAG) methods Solve industry relevant problems Design and implement artificial intelligence systems and applications that can simulate human intelligence processes through the creation and validation of algorithms … Software Engineering background in C++, Python or similar NLP Tasks (Natural Language Processing) Experience with LLMs (Large Language Models) Hands on experience with RAG techniques (Retrieval Augmented Generation) Generative AI Job Offer Private Medical Bonus (18%) Private Pension 25 days + BHs Flexible working More ❯

Experience working in cloud environments (AWS, GCP, or Azure) Ability to work independently and communicate effectively in a remote team Bonus Points Experience with Hugging Face Transformers , LangChain , or RAG pipelines Knowledge of MLOps tools (e.g. MLflow, Weights & Biases, Docker, Kubernetes) Exposure to data engineering or DevOps practices Contributions to open-source AI projects or research publications What We Offer More ❯

secure cloud development practices and IAM role design. Understanding of LLM fine-tuning, embeddings, vector stores (e.g., Pinecone, FAISS, OpenSearch). Exposure to contact centre automation, conversational agents, or RAG pipelines. Adecco is a disability-confident employer. It is important to us that we run an inclusive and accessible recruitment process to support candidates of all backgrounds and all abilities More ❯

team building scalable GenAI solutions, architect Agentic AI components, and integrate them into enterprise systems.Skills- Strong experience in full-stack and cloud-native engineering (Azure preferred) Expertise in GenAI (RAG, prompt engineering, LLM APIs) Deep knowledge of Agentic AI systems and orchestration Proficiency in Python, SQL, NodeJS (React is a plus) Agile leadership and stakeholder collaboration skills Details- 6 month More ❯

working with a small, agile team focused on deploying open-source models into production environments.?? Key Responsibilities Fine-tune and evaluate LLMs for domain-specific tasks Build and optimise RAG pipelines using vector databases Develop prompt engineering strategies and orchestration flows Integrate models into backend services via APIs Implement evaluation frameworks for response quality and reliability Essential Skills Strong Python More ❯

Architect multi-step agent workflows using: Semantic Kernel SDK (C# or Python) Azure OpenAI (GPT-4, function calling, chat completion) Planner and Kernel Memory APIs for reasoning and memory RAG pipelines grounded in enterprise data via Azure AI Search Microsoft 365 & Graph API Integration Enable agents to access and reason over content in: SharePoint, OneDrive, Teams, Outlook, and Planner Use More ❯

optimized for complex financial workflows Event-driven distributed systems handling sensitive data at enterprise scale The Tech Stack AI/ML : Multi-agent frameworks, fine-tuning, reinforcement learning, advanced RAG Platform : AWS serverless, event-driven architecture, microservices Languages : Python, with modern ML libraries (PyTorch, TensorFlow) What They're Looking For 5+ years developing AI/ML systems beyond basic integration More ❯

backend engineering , ideally with Go and ML frameworks like PyTorch or TensorFlow Familiarity with MLOps , cloud infrastructure (AWS) , Kubernetes , and Terraform Experience evaluating and deploying models (including anomaly detection, RAG, and clustering) in noisy, evolving data environments Nice to Have: Experience with Perl Knowledge of threat intelligence integration and MCP architectures Location: Remote Salary: Up to £120,000 , depending on More ❯

data team and creating a culture that enables growth, development and psychological safety Exploring and applying Large Language Models (LLMs) and other modern AI techniques (e.g., embeddings, retrieval-augmented generation, summarisation) to enhance internal tools, automate workflows, or develop client-facing features Acquiring, cleaning, and integrating data from internal and external sources to enrich More ❯

data team and creating a culture that enables growth, development and psychological safety Exploring and applying Large Language Models (LLMs) and other modern AI techniques (e.g., embeddings, retrieval-augmented generation, summarisation) to enhance internal tools, automate workflows, or develop client-facing features Acquiring, cleaning, and integrating data from internal and external sources to enrich More ❯

learning theories, and pedagogical best practices; Engineer context structures integrating with existing curricula and learning pathways; Develop dynamic frameworks adapting to diverse cultural and educational contexts Build and optimize RAG systems for intelligent content surfacing; Design multi-modal context systems integrating text, audio, visual elements; Implement real-time context adaptation based on learner progress Curate and structure educational content repositories … successful in this role, you will ideally have/be: AI/ML fundamentals including LLMs, NLP, and system architecture Programming proficiency in Python with AI/ML frameworks RAG systems and vector database experience Previous experience in educational technology, AI/ML applications, or digital learning product development (desirable) Proven experience in database design, API development, and data pipeline More ❯

part of a small, elite, cross-functional team. What You’ll Be Doing: Designing and implementing NLP pipelines for transcription, topic extraction, and summarisation Developing modular LLM workflows (e.g., RAG, graph-based reasoning) optimised for low-resource deployments Integrating structured and unstructured data: transcripts, policy documents, supply chain models Collaborating with platform engineers to containerise models for edge inference Defining … experience building and deploying NLP/LLM solutions, including summarisation, entity extraction, and topic modelling Strong Python skills with libraries such as HuggingFace Transformers, spaCy, PyTorch/TensorFlow, or RAG frameworks Experience with knowledge graphs, GNNs, or graph-enabled retrieval Proven ability to optimise ML systems for air-gapped, low-compute, or edge environments Understanding of evaluation methods More ❯

high-performance services using Golang in secure environments Develop ingestion and processing pipelines for transcription and structured/unstructured data Contribute to intelligent data flows including graph-based and RAG inference pipelines Expose well-structured APIs to support real-time dashboards and NLP workflows Deploy and scale systems using Kubernetes and Docker Collaborate with platform and data science teams to … orchestration tooling (e.g. Argo), and Kafka or equivalent Strong database knowledge (Postgres preferred) Ability to design and scale APIs and backend pipelines for data-rich environments Bonus: Familiarity with RAG pipelines, transcription tooling, vector DBs, or LLM deployment Bonus: Prior experience within Defence, aerospace, or highly regulated industries Why It Stands Out: This isnt a generic software build. Youll help More ❯

high-performance services using Golang in secure environments Develop ingestion and processing pipelines for transcription and structured/unstructured data Contribute to intelligent data flows including graph-based and RAG inference pipelines Expose well-structured APIs to support real-time dashboards and NLP workflows Deploy and scale systems using Kubernetes and Docker Collaborate with platform and data science teams to … orchestration tooling (e.g. Argo), and Kafka or equivalent Strong database knowledge (Postgres preferred) Ability to design and scale APIs and backend pipelines for data-rich environments Bonus: Familiarity with RAG pipelines, transcription tooling, vector DBs, or LLM deployment Bonus: Prior experience within Defence, aerospace, or highly regulated industries Why It Stands Out: This isn’t a generic software build. You More ❯