1 to 25 of 204 Retrieval-Augmented Generation Jobs in the South East

What You’ll Be Doing Designing, developing, and deploying AI and LLM-based solutions in production environments Building and maintaining retrieval-augmented generation (RAG) pipelines and integrating LLM APIs (e.g. GPT, Claude, Gemini) Developing and optimising APIs, embeddings, and backend services for AI systems Writing clean, efficient, and well-documented code in Python and … the UK (visa sponsorship not available) Nice to Have Experience with prompt engineering , fine-tuning , or AI agents Understanding of retrieval-augmented generation (RAG) systems and semantic search Exposure to enterprise AI security , multimodal AI , or reinforcement learning (RLHF) Benefits 💰 Competitive Salary: Up to £70,000 + annual performance bonus 🏡 Hybrid Working: Flexible blend More ❯

What You’ll Be Doing Designing, developing, and deploying AI and LLM-based solutions in production environments Building and maintaining retrieval-augmented generation (RAG) pipelines and integrating LLM APIs (e.g. GPT, Claude, Gemini) Developing and optimising APIs, embeddings, and backend services for AI systems Writing clean, efficient, and well-documented code in Python and … the UK (visa sponsorship not available) Nice to Have Experience with prompt engineering , fine-tuning , or AI agents Understanding of retrieval-augmented generation (RAG) systems and semantic search Exposure to enterprise AI security , multimodal AI , or reinforcement learning (RLHF) Benefits 💰 Competitive Salary: Up to £70,000 + annual performance bonus 🏡 Hybrid Working: Flexible blend More ❯

/ML systems for business intelligence. Build robust APIs, microservices, and data pipelines to power intelligent, data-driven tools. Develop retrieval-augmented generation (RAG) systems using vector databases for contextual AI. Set the technical direction for backend and AI integration best practices. Partner with cross-functional teams to identify and deliver high-value AI … the ability to translate technical outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and comprehensive benefits package 25 days annual More ❯

/ML systems for business intelligence. Build robust APIs, microservices, and data pipelines to power intelligent, data-driven tools. Develop retrieval-augmented generation (RAG) systems using vector databases for contextual AI. Set the technical direction for backend and AI integration best practices. Partner with cross-functional teams to identify and deliver high-value AI … the ability to translate technical outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and comprehensive benefits package 25 days annual More ❯

/ML systems for business intelligence. Build robust APIs, microservices, and data pipelines to power intelligent, data-driven tools. Develop retrieval-augmented generation (RAG) systems using vector databases for contextual AI. Set the technical direction for backend and AI integration best practices. Partner with cross-functional teams to identify and deliver high-value AI … the ability to translate technical outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and comprehensive benefits package 25 days annual More ❯

/ML systems for business intelligence. Build robust APIs, microservices, and data pipelines to power intelligent, data-driven tools. Develop retrieval-augmented generation (RAG) systems using vector databases for contextual AI. Set the technical direction for backend and AI integration best practices. Partner with cross-functional teams to identify and deliver high-value AI … the ability to translate technical outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and comprehensive benefits package 25 days annual More ❯

/ML systems for business intelligence. Build robust APIs, microservices, and data pipelines to power intelligent, data-driven tools. Develop retrieval-augmented generation (RAG) systems using vector databases for contextual AI. Set the technical direction for backend and AI integration best practices. Partner with cross-functional teams to identify and deliver high-value AI … the ability to translate technical outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and comprehensive benefits package 25 days annual More ❯

/ML systems for business intelligence. Build robust APIs, microservices, and data pipelines to power intelligent, data-driven tools. Develop retrieval-augmented generation (RAG) systems using vector databases for contextual AI. Set the technical direction for backend and AI integration best practices. Partner with cross-functional teams to identify and deliver high-value AI … the ability to translate technical outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and comprehensive benefits package 25 days annual More ❯

real-world applications. Develop and optimise pipelines for data collection, preprocessing, and model evaluation. Collaborate with product engineers to deploy models into scalable production systems. Experiment with prompt engineering, RAG architectures, and multimodal models. Contribute to internal tools for monitoring, testing, and improving AI performance. Stay on the edge of ML/AI research — we give you time and resources … to PyTorch/TensorFlow/Hugging Face. (Bonus) understand fundamentals of deep learning, LLMs, and MLOps, vector databases, embeddings, or retrieval-augmented generation (RAG). Loves solving complex problems and thrives in a fast-moving startup environment. Is curious, ambitious, and eager to build real AI systems that have an impact. What You’ll … LLM Engineer, AI Engineer, Artificial Intelligence, Deep Learning, NLP, Natural Language Processing, Large Language Models, Generative AI, GenAI, Neural Networks, PyTorch, TensorFlow, Hugging Face, OpenAI, LangChain, RAG, Retrieval-Augmented Generation, Python, Data Science, AI Research, MLOps, Data Pipelines, Prompt Engineering, Model Fine-Tuning, Cloud Computing, AWS, Azure, Google Cloud, AI Infrastructure, Transformers, Reinforcement Learning More ❯

and frame AI use cases Prototype multi-agent systems, reasoning engines, and knowledge-graph integrations Implement and fine-tune models for language understanding, decision automation, and data insight generation Evaluate and integrate open-source and commercial AI frameworks into orchestration workflows Ensure AI solutions are explainable, auditable, and compliant with public- sector governance standards Advise on AI strategy … Python and popular AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face) Familiarity with LLM fine-tuning, reasoning, and retrieval-augmented generation (RAG) techniques Experience integrating AI models into production systems or orchestration platforms Strong analytical and problem-solving skills, with the ability to translate research into practical outcomes Excellent written and verbal … recruitment keywords: Artificial intelligence large language models AI machine learning Agentic AI multi-agent Python AI/ML PyTorch TensorFlow LangChain Hugging Face LLM retrieval augmented generation RAG AI models orchestration platforms Public sector SC Security Clearance agent architectures ReAct AutoGen CrewAI BabyAGI reasoning loops memory systems governance frameworks public-sector AI standards BPMN More ❯

and frame AI use cases Prototype multi-agent systems, reasoning engines, and knowledge-graph integrations Implement and fine-tune models for language understanding, decision automation, and data insight generation Evaluate and integrate open-source and commercial AI frameworks into orchestration workflows Ensure AI solutions are explainable, auditable, and compliant with public- sector governance standards Advise on AI strategy … Python and popular AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face) Familiarity with LLM fine-tuning, reasoning, and retrieval-augmented generation (RAG) techniques Experience integrating AI models into production systems or orchestration platforms Strong analytical and problem-solving skills, with the ability to translate research into practical outcomes Excellent written and verbal … recruitment keywords: Artificial intelligence large language models AI machine learning Agentic AI multi-agent Python AI/ML PyTorch TensorFlow LangChain Hugging Face LLM retrieval augmented generation RAG AI models orchestration platforms Public sector SC Security Clearance agent architectures ReAct AutoGen CrewAI BabyAGI reasoning loops memory systems governance frameworks public-sector AI standards BPMN More ❯

and frame AI use cases Prototype multi-agent systems, reasoning engines, and knowledge-graph integrations Implement and fine-tune models for language understanding, decision automation, and data insight generation Evaluate and integrate open-source and commercial AI frameworks into orchestration workflows Ensure AI solutions are explainable, auditable, and compliant with public- sector governance standards Advise on AI strategy … Python and popular AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face) Familiarity with LLM fine-tuning, reasoning, and retrieval-augmented generation (RAG) techniques Experience integrating AI models into production systems or orchestration platforms Strong analytical and problem-solving skills, with the ability to translate research into practical outcomes Excellent written and verbal … recruitment keywords: Artificial intelligence large language models AI machine learning Agentic AI multi-agent Python AI/ML PyTorch TensorFlow LangChain Hugging Face LLM retrieval augmented generation RAG AI models orchestration platforms Public sector SC Security Clearance agent architectures ReAct AutoGen CrewAI BabyAGI reasoning loops memory systems governance frameworks public-sector AI standards BPMN More ❯

and frame AI use cases Prototype multi-agent systems, reasoning engines, and knowledge-graph integrations Implement and fine-tune models for language understanding, decision automation, and data insight generation Evaluate and integrate open-source and commercial AI frameworks into orchestration workflows Ensure AI solutions are explainable, auditable, and compliant with public- sector governance standards Advise on AI strategy … Python and popular AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face) Familiarity with LLM fine-tuning, reasoning, and retrieval-augmented generation (RAG) techniques Experience integrating AI models into production systems or orchestration platforms Strong analytical and problem-solving skills, with the ability to translate research into practical outcomes Excellent written and verbal … recruitment keywords: Artificial intelligence large language models AI machine learning Agentic AI multi-agent Python AI/ML PyTorch TensorFlow LangChain Hugging Face LLM retrieval augmented generation RAG AI models orchestration platforms Public sector SC Security Clearance agent architectures ReAct AutoGen CrewAI BabyAGI reasoning loops memory systems governance frameworks public-sector AI standards BPMN More ❯

tune LLM-based applications such as: - Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores using Python, Java, or Node.js. Collaborate with architects to define … optimization. Ensure compliance with AI ethics, security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic search and retrieval. Partner with business stakeholders to identify and shape impactful AI use cases. Contribute to … Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Vertex AI, Azure More ❯

tune LLM-based applications such as: - Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores using Python, Java, or Node.js. Collaborate with architects to define … optimization. Ensure compliance with AI ethics, security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic search and retrieval. Partner with business stakeholders to identify and shape impactful AI use cases. Contribute to … Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Vertex AI, Azure More ❯

tune LLM-based applications such as: - Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores using Python, Java, or Node.js. Collaborate with architects to define … optimization. Ensure compliance with AI ethics, security, and governance standards. Prepare and curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic search and retrieval. Partner with business stakeholders to identify and shape impactful AI use cases. Contribute to … Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Vertex AI, Azure More ❯

systems and agentic applications that drive meaningful business outcomes. The Role As our Generative AI Engineer , you’ll be at the forefront of innovation, designing and deploying next-generation AI systems using large language models (LLMs), multi-agent frameworks, and cutting-edge GenAI tooling. You’ll partner closely with stakeholders across Product, Design, and Operations to translate business … AI use cases, translate requirements, and deliver solutions that align with business goals. Develop and fine-tune LLMs and implement Retrieval-Augmented Generation (RAG) pipelines for specialized knowledge tasks. Engineer agentic workflows , including hierarchical agents, swarms, and complex coordination logic for multi-tasking and automation. Integrate GenAI tools into platforms such as WordPress and … proficient in libraries such as NumPy, Pandas, scikit-learn, PyTorch, TensorFlow. Proven experience building and scaling GenAI applications in production. Expertise in LLM architectures (OpenAI, LLaMA, Mistral, etc.) and RAG implementation. Familiarity with frameworks like LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker More ❯

systems and agentic applications that drive meaningful business outcomes. The Role As our Generative AI Engineer , you’ll be at the forefront of innovation, designing and deploying next-generation AI systems using large language models (LLMs), multi-agent frameworks, and cutting-edge GenAI tooling. You’ll partner closely with stakeholders across Product, Design, and Operations to translate business … AI use cases, translate requirements, and deliver solutions that align with business goals. Develop and fine-tune LLMs and implement Retrieval-Augmented Generation (RAG) pipelines for specialized knowledge tasks. Engineer agentic workflows , including hierarchical agents, swarms, and complex coordination logic for multi-tasking and automation. Integrate GenAI tools into platforms such as WordPress and … proficient in libraries such as NumPy, Pandas, scikit-learn, PyTorch, TensorFlow. Proven experience building and scaling GenAI applications in production. Expertise in LLM architectures (OpenAI, LLaMA, Mistral, etc.) and RAG implementation. Familiarity with frameworks like LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker More ❯

systems and agentic applications that drive meaningful business outcomes. The Role As our Generative AI Engineer , you’ll be at the forefront of innovation, designing and deploying next-generation AI systems using large language models (LLMs), multi-agent frameworks, and cutting-edge GenAI tooling. You’ll partner closely with stakeholders across Product, Design, and Operations to translate business … AI use cases, translate requirements, and deliver solutions that align with business goals. Develop and fine-tune LLMs and implement Retrieval-Augmented Generation (RAG) pipelines for specialized knowledge tasks. Engineer agentic workflows , including hierarchical agents, swarms, and complex coordination logic for multi-tasking and automation. Integrate GenAI tools into platforms such as WordPress and … proficient in libraries such as NumPy, Pandas, scikit-learn, PyTorch, TensorFlow. Proven experience building and scaling GenAI applications in production. Expertise in LLM architectures (OpenAI, LLaMA, Mistral, etc.) and RAG implementation. Familiarity with frameworks like LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker More ❯

Model Context Protocol for managing context and tool interfaces for agents. LLM integration patterns, including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). Preferred Skills Preferred knowledge of More ❯

Model Context Protocol for managing context and tool interfaces for agents. LLM integration patterns, including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). Preferred Skills Preferred knowledge of More ❯

Model Context Protocol for managing context and tool interfaces for agents. LLM integration patterns, including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). Preferred Skills Preferred knowledge of More ❯

production-grade LLM applications on Azure. You’ll work on AI-enabled and augmented intelligence solutions such as retrieval-augmented generation (RAG), agentic workflows, and model integrations with a strong emphasis on reliability, performance, security, and continuous improvement. Main Duties and Responsibilities Data & Retrieval Build robust ingestion pipelines for PDFs …/Word/Excel/Audio/JSON and semi-structured sources. Design RAG systems : chunking strategies, document schemas, metadata, hybrid/dense retrieval, re-ranking, and grounding. Manage vector/keyword indexes (e.g., Azure AI Search , pgvector, Pinecone/Weaviate). Develop and deploy advanced NLP, information retrieval, and recommendation systems that enhance Chambers and … Vault , private networking. Add observability : tracing/telemetry (OpenTelemetry, LangSmith), metrics, logs, cost and token usage monitoring, alerts. Apply evaluation & QA : regression suites, offline eval sets/golden data, RAG evals (faithfulness, answer relevance, citation correctness), A/B tests, win-rate testing. Ensure reliability : rate-limit handling, retries/backoff, idempotency, circuit breakers, caching (e.g., Redis/semantic cache More ❯

AI Technical Consultant Engineer L LM, Python, RAG, Data Analyst – SQL, Tableau, R, Python, Gen AI & Machine Learning. Hybrid working, office location Weybridge, Surrey. The role: Build and refine LLM/SLM-based Generative AI solutions from scratch, including retrieval-augmented generation (RAG), fine-tuning, and prompt engineering. Design and oversee solution architecture for More ❯

AI Technical Consultant Engineer L LM, Python, RAG, Data Analyst – SQL, Tableau, R, Python, Gen AI & Machine Learning. Hybrid working, office location Weybridge, Surrey. The role: Build and refine LLM/SLM-based Generative AI solutions from scratch, including retrieval-augmented generation (RAG), fine-tuning, and prompt engineering. Design and oversee solution architecture for More ❯