151 to 175 of 222 Retrieval-Augmented Generation Jobs in the South East

ML systems Deep knowledge of LLM architectures and attention mechanisms – experienced with MoE, MHA, SWA, Flash Attention, GPT, LLaMA, DeepSeek, and reasoning-based models Experience in creating and maintaining RAG supported systems including PDF extraction, OCR, and varying chunking and embedding methodologies Inference optimisation experience – hands-on with high-performance inference frameworks such as vLLM, TensorRT, and related acceleration techniques … Proven evaluation experience – successfully conducted assessments of RAG and agentic systems. Both on performance and compliance (harm, guardrails, etc) 4+ years of development competency across a variety of languages, frameworks, and tooling, such as Python, R, Kubernetes, Kubeflow, JavaScript/JVM, Kafka Background in Application development, deployment, and monitoring on Kubernetes Proficient in PyTorch or similar frameworks (e.g Tensorflow) – demonstrates More ❯

ML systems Deep knowledge of LLM architectures and attention mechanisms – experienced with MoE, MHA, SWA, Flash Attention, GPT, LLaMA, DeepSeek, and reasoning-based models Experience in creating and maintaining RAG supported systems including PDF extraction, OCR, and varying chunking and embedding methodologies Inference optimisation experience – hands-on with high-performance inference frameworks such as vLLM, TensorRT, and related acceleration techniques … Proven evaluation experience – successfully conducted assessments of RAG and agentic systems. Both on performance and compliance (harm, guardrails, etc) 4+ years of development competency across a variety of languages, frameworks, and tooling, such as Python, R, Kubernetes, Kubeflow, JavaScript/JVM, Kafka Background in Application development, deployment, and monitoring on Kubernetes Proficient in PyTorch or similar frameworks (e.g Tensorflow) – demonstrates More ❯

ML systems Deep knowledge of LLM architectures and attention mechanisms – experienced with MoE, MHA, SWA, Flash Attention, GPT, LLaMA, DeepSeek, and reasoning-based models Experience in creating and maintaining RAG supported systems including PDF extraction, OCR, and varying chunking and embedding methodologies Inference optimisation experience – hands-on with high-performance inference frameworks such as vLLM, TensorRT, and related acceleration techniques … Proven evaluation experience – successfully conducted assessments of RAG and agentic systems. Both on performance and compliance (harm, guardrails, etc) 4+ years of development competency across a variety of languages, frameworks, and tooling, such as Python, R, Kubernetes, Kubeflow, JavaScript/JVM, Kafka Background in Application development, deployment, and monitoring on Kubernetes Proficient in PyTorch or similar frameworks (e.g Tensorflow) – demonstrates More ❯

LangChain, Hugging Face, etc.) and enterprise platforms (Azure OpenAI, Databricks, etc.) to deliver production ready, scalable AI solutions Implement generative AI and advanced analytics features, including embeddings, retrieval-augmented generation, and building AI agents and chat-based solutions. Write clean, testable, and well-documented code using modern engineering practices (unit testing, code reviews, API More ❯

production-grade code shipping. Applied LLMs - Experience deploying multimodal foundation model-based products. Deep knowledge of LLM research, agents, tools, and function calling. Deploying LLMs - Experience with LangChain, indexing, RAG, semantic search, and fine-tuning (SFT/RL) of LLMs/agents. Why Join £100,000 – £170,000 base salary + meaningful equity Visa sponsorship and relocation support available A More ❯

production-grade code shipping. Applied LLMs - Experience deploying multimodal foundation model-based products. Deep knowledge of LLM research, agents, tools, and function calling. Deploying LLMs - Experience with LangChain, indexing, RAG, semantic search, and fine-tuning (SFT/RL) of LLMs/agents. Why Join £100,000 – £170,000 base salary + meaningful equity Visa sponsorship and relocation support available A More ❯

production-grade code shipping. Applied LLMs - Experience deploying multimodal foundation model-based products. Deep knowledge of LLM research, agents, tools, and function calling. Deploying LLMs - Experience with LangChain, indexing, RAG, semantic search, and fine-tuning (SFT/RL) of LLMs/agents. Why Join £100,000 – £170,000 base salary + meaningful equity Visa sponsorship and relocation support available A More ❯

a successful, the ideal Senior Software Engineer candidate will have: · A deep experience of working on backend projects with Typescript and Node · Strong experience with Python/LLMs and RAG · Experience of building products that customers will love to use · Experience of working in a small team and getting things done If you are an ambitious Senior Software Engineer hit More ❯

LLMs, prompt engineering, and agentic AI Desirable: ☑️ Experience with frameworks such as AutoGPT, CrewAI, or LangGraph ☑️ Background in conversational UX or human-AI interaction ☑️ Knowledge of vector databases or RAG techniques ☑️ Awareness of ethical and safety considerations in AI system If you'd like to learn more, feel free to reach out directly or email for a confidential chat. Role More ❯

LLMs, prompt engineering, and agentic AI Desirable: ☑️ Experience with frameworks such as AutoGPT, CrewAI, or LangGraph ☑️ Background in conversational UX or human-AI interaction ☑️ Knowledge of vector databases or RAG techniques ☑️ Awareness of ethical and safety considerations in AI system If you'd like to learn more, feel free to reach out directly or email for a confidential chat. Role More ❯

goes beyond static models to deliver autonomous, measurable business impact. To accelerate this capability, we're hiring a Senior Generative AI Engineer to design, build, and deploy next-generation AI ecosystems for global enterprises. You'll … join a hybrid London team (two days a week on-site) with strong flexibility for remote work. Your Role Design, build, and deploy generative AI systems (LLMs, retrieval-augmented architectures, embedding pipelines, agents) from prototype to production. Lead the full ML lifecycle: data extraction, modelling, fine-tuning, training, inference, deployment, and monitoring. Collaborate with product, engineering … engineers and raise the overall technical bar of the team. You Bring 5+ years of ML/AI engineering experience, including 3+ years deploying generative AI (LLMs, fine-tuning, RAG) in production. Strong technical grounding in Python, TensorFlow/PyTorch, transformer architectures (GPT, Llama, Mistral), vector databases, and prompt engineering frameworks. Proven record of delivering measurable ROI from AI projects. More ❯

Lead AI Engineer/Consultant - Greenfield Outside IR35 £600 - £750pd flexible for the right person RAG experience a must. About the Company Market leading SaaS organisation building out their AI function. About the Role This project is a greenfield build out of AI capabilities. They are starting with RAG use cases as a low bar, but are targeting a rich … deliver an AI capability. Lead design, architecture, and delivery of advanced AI/ML and generative AI solutions, ensuring scalable, secure, and production-ready system. Expert in MCP and RAG patterns. Design and build robust data and ingestion pipelines, integrate vector databases, and RSG. Expert-level proficiency in Python and key ML libraries (Langchain, Semantic Kernel, PyTorch, TensorFlow). Hands … complex, data-rich environments. Skilled in setting team engineering practices: Git, CI/CD, automated testing for ML code, code reviews, and documentation. Preferred Skills Expert in MCP and RAG patterns . Experience in developing agentic AI systems Lead tech enablement and mentor engineers, fostering culture of reliability, continuous improvement, and collaboration. Excellent communication skills, able to translate technical strategy More ❯

Lead AI Engineer/Consultant - Greenfield Outside IR35 £600 - £750pd flexible for the right person RAG experience a must. About the Company Market leading SaaS organisation building out their AI function. About the Role This project is a greenfield build out of AI capabilities. They are starting with RAG use cases as a low bar, but are targeting a rich … deliver an AI capability. Lead design, architecture, and delivery of advanced AI/ML and generative AI solutions, ensuring scalable, secure, and production-ready system. Expert in MCP and RAG patterns. Design and build robust data and ingestion pipelines, integrate vector databases, and RSG. Expert-level proficiency in Python and key ML libraries (Langchain, Semantic Kernel, PyTorch, TensorFlow). Hands … complex, data-rich environments. Skilled in setting team engineering practices: Git, CI/CD, automated testing for ML code, code reviews, and documentation. Preferred Skills Expert in MCP and RAG patterns . Experience in developing agentic AI systems Lead tech enablement and mentor engineers, fostering culture of reliability, continuous improvement, and collaboration. Excellent communication skills, able to translate technical strategy More ❯

Lead AI Engineer/Consultant - Greenfield Outside IR35 £600 - £750pd flexible for the right person RAG experience a must. About the Company Market leading SaaS organisation building out their AI function. About the Role This project is a greenfield build out of AI capabilities. They are starting with RAG use cases as a low bar, but are targeting a rich … deliver an AI capability. Lead design, architecture, and delivery of advanced AI/ML and generative AI solutions, ensuring scalable, secure, and production-ready system. Expert in MCP and RAG patterns. Design and build robust data and ingestion pipelines, integrate vector databases, and RSG. Expert-level proficiency in Python and key ML libraries (Langchain, Semantic Kernel, PyTorch, TensorFlow). Hands … complex, data-rich environments. Skilled in setting team engineering practices: Git, CI/CD, automated testing for ML code, code reviews, and documentation. Preferred Skills Expert in MCP and RAG patterns . Experience in developing agentic AI systems Lead tech enablement and mentor engineers, fostering culture of reliability, continuous improvement, and collaboration. Excellent communication skills, able to translate technical strategy More ❯

function Comfort working in a fast-moving, ambiguous environment An eye for quality and a bias toward shipping Bonus: experience in building AI-powered tools or creative applications (e.g. RAG systems, assistants, agents, etc. More ❯

function Comfort working in a fast-moving, ambiguous environment An eye for quality and a bias toward shipping Bonus: experience in building AI-powered tools or creative applications (e.g. RAG systems, assistants, agents, etc. More ❯

function Comfort working in a fast-moving, ambiguous environment An eye for quality and a bias toward shipping Bonus: experience in building AI-powered tools or creative applications (e.g. RAG systems, assistants, agents, etc. More ❯

expertise and strategic thinking. What You’ll Do Design, build, and deploy AI-powered systems and features that enhance product functionality and user experience. Develop and integrate agentic frameworks, RAG pipelines, and vector database architectures to support natural language and intelligent automation use cases. Fine-tune and customise LLMs (e.g. OpenAI, Anthropic, and other models) for specific business applications. Collaborate … and scaling AI models in Azure and/or AWS environments. Skilled in using LangChain, LangGraph, vector databases, and prompt engineering. Understanding of LLM optimisation, including context extension and RAG-based frameworks. Proven ability to collaborate cross-functionally and communicate complex AI concepts to non-technical teams. A proactive, creative mindset — comfortable operating with autonomy to build scalable, production-grade … Why This Role Play a central role in defining and executing an organisation-wide AI roadmap. Work directly with senior leadership on strategy and implementation. Shape the next generation of intelligent, data-driven products. Hybrid working environment with flexibility for deep technical focus and collaboration. Competitive compensation and the opportunity to build at scale in a high-growth More ❯

expertise and strategic thinking. What You’ll Do Design, build, and deploy AI-powered systems and features that enhance product functionality and user experience. Develop and integrate agentic frameworks, RAG pipelines, and vector database architectures to support natural language and intelligent automation use cases. Fine-tune and customise LLMs (e.g. OpenAI, Anthropic, and other models) for specific business applications. Collaborate … and scaling AI models in Azure and/or AWS environments. Skilled in using LangChain, LangGraph, vector databases, and prompt engineering. Understanding of LLM optimisation, including context extension and RAG-based frameworks. Proven ability to collaborate cross-functionally and communicate complex AI concepts to non-technical teams. A proactive, creative mindset — comfortable operating with autonomy to build scalable, production-grade … Why This Role Play a central role in defining and executing an organisation-wide AI roadmap. Work directly with senior leadership on strategy and implementation. Shape the next generation of intelligent, data-driven products. Hybrid working environment with flexibility for deep technical focus and collaboration. Competitive compensation and the opportunity to build at scale in a high-growth More ❯

expertise and strategic thinking. What You’ll Do Design, build, and deploy AI-powered systems and features that enhance product functionality and user experience. Develop and integrate agentic frameworks, RAG pipelines, and vector database architectures to support natural language and intelligent automation use cases. Fine-tune and customise LLMs (e.g. OpenAI, Anthropic, and other models) for specific business applications. Collaborate … and scaling AI models in Azure and/or AWS environments. Skilled in using LangChain, LangGraph, vector databases, and prompt engineering. Understanding of LLM optimisation, including context extension and RAG-based frameworks. Proven ability to collaborate cross-functionally and communicate complex AI concepts to non-technical teams. A proactive, creative mindset — comfortable operating with autonomy to build scalable, production-grade … Why This Role Play a central role in defining and executing an organisation-wide AI roadmap. Work directly with senior leadership on strategy and implementation. Shape the next generation of intelligent, data-driven products. Hybrid working environment with flexibility for deep technical focus and collaboration. Competitive compensation and the opportunity to build at scale in a high-growth More ❯

researchers, engineers, and portfolio specialists, solving complex real-world problems. Competitive compensation with a performance-linked bonus. What You’ll Do Take ownership of designing and building next-generation AI systems that make complex financial data instantly accessible and actionable. Partner closely with data scientists, ML researchers, and frontend engineers to turn research concepts into robust, scalable production … deployment practices using Docker, Kubernetes, and CI/CD pipelines. Comfort working in cloud-based environments (AWS preferred), including data connectivity and infrastructure-as-code principles. Experience integrating LLMs, RAG pipelines, or vector databases into production workflows is a major plus. A strong communicator who can translate technical complexity into business value and thrives in collaborative, cross-functional environments. Passion More ❯

researchers, engineers, and portfolio specialists, solving complex real-world problems. Competitive compensation with a performance-linked bonus. What You’ll Do Take ownership of designing and building next-generation AI systems that make complex financial data instantly accessible and actionable. Partner closely with data scientists, ML researchers, and frontend engineers to turn research concepts into robust, scalable production … deployment practices using Docker, Kubernetes, and CI/CD pipelines. Comfort working in cloud-based environments (AWS preferred), including data connectivity and infrastructure-as-code principles. Experience integrating LLMs, RAG pipelines, or vector databases into production workflows is a major plus. A strong communicator who can translate technical complexity into business value and thrives in collaborative, cross-functional environments. Passion More ❯

researchers, engineers, and portfolio specialists, solving complex real-world problems. Competitive compensation with a performance-linked bonus. What You’ll Do Take ownership of designing and building next-generation AI systems that make complex financial data instantly accessible and actionable. Partner closely with data scientists, ML researchers, and frontend engineers to turn research concepts into robust, scalable production … deployment practices using Docker, Kubernetes, and CI/CD pipelines. Comfort working in cloud-based environments (AWS preferred), including data connectivity and infrastructure-as-code principles. Experience integrating LLMs, RAG pipelines, or vector databases into production workflows is a major plus. A strong communicator who can translate technical complexity into business value and thrives in collaborative, cross-functional environments. Passion More ❯

feedback loops. 25% Architect & scale Own reliability, latency, and cost. Design online/offline eval harnesses, canaries, and SLAs; operate GPUs/accelerators where needed. Stand up and harden RAG pipelines (indexing, retrieval policies, grounding, guardrails) and agent frameworks. Take basic infra ownership on GCP (or AWS/Azure): networking, autoscaling, CI/CD, IaC, observability, and cost … building production ML/back‐end systems; 2+ years leading while coding. Expert Python ; strong back‐end chops (e.g., FastAPI, gRPC, Postgres, pub/sub/streams). Agents & RAG: Fluency with at least one agent framework ( ADK preferred ). Proven track record shipping AI agents and building RAG pipelines. LLM + DS depth: Prompting/tooling, retrieval More ❯

feedback loops. 25% Architect & scale Own reliability, latency, and cost. Design online/offline eval harnesses, canaries, and SLAs; operate GPUs/accelerators where needed. Stand up and harden RAG pipelines (indexing, retrieval policies, grounding, guardrails) and agent frameworks. Take basic infra ownership on GCP (or AWS/Azure): networking, autoscaling, CI/CD, IaC, observability, and cost … building production ML/back‐end systems; 2+ years leading while coding. Expert Python ; strong back‐end chops (e.g., FastAPI, gRPC, Postgres, pub/sub/streams). Agents & RAG: Fluency with at least one agent framework ( ADK preferred ). Proven track record shipping AI agents and building RAG pipelines. LLM + DS depth: Prompting/tooling, retrieval More ❯