1 to 25 of 103 Remote 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 ❯

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 ❯

about building intelligent, agentic systems using LangGraph. If you thrive at the intersection of LLMs, automation, and complex system design, this is your chance to shape the next generation of AI infrastructure. What You’ll Do Design, implement, and optimize LangGraph-based AI workflows and multi-agent systems Integrate LLMs, APIs, and data pipelines into production-ready solutions … contributions to the open-source project) Strong background in Python, LangChain, OpenAI APIs, and LLM architectures Familiarity with vector databases, retrieval-augmented generation (RAG), and prompt engineering Understanding of software design principles, version control (Git), and CI/CD practices Creative problem-solver with a bias toward action and experimentation Nice to Have Experience More ❯

about building intelligent, agentic systems using LangGraph. If you thrive at the intersection of LLMs, automation, and complex system design, this is your chance to shape the next generation of AI infrastructure. What You’ll Do Design, implement, and optimize LangGraph-based AI workflows and multi-agent systems Integrate LLMs, APIs, and data pipelines into production-ready solutions … contributions to the open-source project) Strong background in Python, LangChain, OpenAI APIs, and LLM architectures Familiarity with vector databases, retrieval-augmented generation (RAG), and prompt engineering Understanding of software design principles, version control (Git), and CI/CD practices Creative problem-solver with a bias toward action and experimentation Nice to Have Experience More ❯

about building intelligent, agentic systems using LangGraph. If you thrive at the intersection of LLMs, automation, and complex system design, this is your chance to shape the next generation of AI infrastructure. What You’ll Do Design, implement, and optimize LangGraph-based AI workflows and multi-agent systems Integrate LLMs, APIs, and data pipelines into production-ready solutions … contributions to the open-source project) Strong background in Python, LangChain, OpenAI APIs, and LLM architectures Familiarity with vector databases, retrieval-augmented generation (RAG), and prompt engineering Understanding of software design principles, version control (Git), and CI/CD practices Creative problem-solver with a bias toward action and experimentation Nice to Have Experience 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 ❯

recruiting on behalf of our global energies client for an NLP/GenAI Data Scientist who can bring a strong understanding in modern NLP, LLMs, transformer architectures, prompt-engineering, RAG, agentic architectures and evaluation methodologies. They require candidates to offer strong knowledge of Python programming for developing and debugging AI models and would expect suitable candidates to be educated to … within the GenAI/NLP team. This role will focus on the application and development of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, and domain-specific GenAI solutions to support key internal use cases and products. Responsibilities In this role you will: Design, implement and maintain scalable NLP and GenAI pipelines (including … to date with state-of-the-art research in the space of LLMs/NLP, proposing new ideas and methodologies that unlock business value. Contribute to the development of RAG systems and retrieval pipelines, including chunking, embedding, re-ranking, and evaluation. Participate in experiments, including designing experimental details, writing reusable code, running evaluations, and organising results. Collaborate with More ❯

recruiting on behalf of our global energies client for an NLP/GenAI Data Scientist who can bring a strong understanding in modern NLP, LLMs, transformer architectures, prompt-engineering, RAG, agentic architectures and evaluation methodologies. They require candidates to offer strong knowledge of Python programming for developing and debugging AI models and would expect suitable candidates to be educated to … within the GenAI/NLP team. This role will focus on the application and development of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, and domain-specific GenAI solutions to support key internal use cases and products. Responsibilities In this role you will: Design, implement and maintain scalable NLP and GenAI pipelines (including … to date with state-of-the-art research in the space of LLMs/NLP, proposing new ideas and methodologies that unlock business value. Contribute to the development of RAG systems and retrieval pipelines, including chunking, embedding, re-ranking, and evaluation. Participate in experiments, including designing experimental details, writing reusable code, running evaluations, and organising results. Collaborate with More ❯

development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects end-to-end Experience with Retrieval-Augmented Generation (RAG) Experience with Azure AI Foundry would be beneficial Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills More ❯

development! Requirements: Strong Python scripting skills Strong understanding of LLMs Experience delivering Gen-AI projects end-to-end Experience with Retrieval-Augmented Generation (RAG) Experience with Azure AI Foundry would be beneficial Experience with Microsoft data technologies would be beneficial Experience with Cloud platforms - ideally Azure Strong communication, stakeholder management and problem-solving skills More ❯