226 to 250 of 358 Retrieval-Augmented Generation Jobs in London

semantic layers using dbt and Delta Live Tables to ensure consistency across analytics and AI use cases Enable Generative AI and ML workloads by designing pipelines for vector search, RAG, and feature engineering Implement secure access and governance controls including RBAC, SSO, token policies, and pseudonymisation frameworks Support batch and streaming data flows using technologies like Kafka, Airflow, and Terraform More ❯

semantic layers using dbt and Delta Live Tables to ensure consistency across analytics and AI use cases Enable Generative AI and ML workloads by designing pipelines for vector search, RAG, and feature engineering Implement secure access and governance controls including RBAC, SSO, token policies, and pseudonymisation frameworks Support batch and streaming data flows using technologies like Kafka, Airflow, and Terraform More ❯

distributed systems and AI research. You'll have 2+ years of professional experience in big tech or start-up Proficiency in Python Strong hands on expertise with LLMs and RAG Traditional ML experience Based in London and in office by default Looking to throw everything into a business from the early days This is an exciting opportunity to join a More ❯

distributed systems and AI research. You'll have 2+ years of professional experience in big tech or start-up Proficiency in Python Strong hands on expertise with LLMs and RAG Traditional ML experience Based in London and in office by default Looking to throw everything into a business from the early days This is an exciting opportunity to join a More ❯

distributed systems and AI research. You'll have 2+ years of professional experience in big tech or start-up Proficiency in Python Strong hands on expertise with LLMs and RAG Traditional ML experience Based in London and in office by default Looking to throw everything into a business from the early days This is an exciting opportunity to join a More ❯

distributed systems and AI research. You'll have 2+ years of professional experience in big tech or start-up Proficiency in Python Strong hands on expertise with LLMs and RAG Traditional ML experience Based in London and in office by default Looking to throw everything into a business from the early days This is an exciting opportunity to join a More ❯

distributed systems and AI research. You'll have 2+ years of professional experience in big tech or start-up Proficiency in Python Strong hands on expertise with LLMs and RAG Traditional ML experience Based in London and in office by default Looking to throw everything into a business from the early days This is an exciting opportunity to join a More ❯

considerations in deploying AI systems. Desirable: Experience with agentic AI frameworks (e.g. AutoGPT, CrewAI, LangGraph, ReAct). Background in conversational design, human-AI interaction, or reinforcement learning. Familiarity with RAG, vector databases, or simulation environments. More ❯

considerations in deploying AI systems. Desirable: Experience with agentic AI frameworks (e.g. AutoGPT, CrewAI, LangGraph, ReAct). Background in conversational design, human-AI interaction, or reinforcement learning. Familiarity with RAG, vector databases, or simulation environments. More ❯

considerations in deploying AI systems. Desirable: Experience with agentic AI frameworks (e.g. AutoGPT, CrewAI, LangGraph, ReAct). Background in conversational design, human-AI interaction, or reinforcement learning. Familiarity with RAG, vector databases, or simulation environments. More ❯

considerations in deploying AI systems. Desirable: Experience with agentic AI frameworks (e.g. AutoGPT, CrewAI, LangGraph, ReAct). Background in conversational design, human-AI interaction, or reinforcement learning. Familiarity with RAG, vector databases, or simulation environments. More ❯

Storage , Queues , and SQL/NoSQL databases to build scalable, event-driven systems. Design and optimise APIs that serve our mobile and web products, including partner integrations. Implement efficient RAG AI backend systems for introducing advanced LLM based features Collaborate with product managers, data engineers, and frontend developers to deliver new features end to end. Write clean, maintainable, and well More ❯

Storage , Queues , and SQL/NoSQL databases to build scalable, event-driven systems. Design and optimise APIs that serve our mobile and web products, including partner integrations. Implement efficient RAG AI backend systems for introducing advanced LLM based features Collaborate with product managers, data engineers, and frontend developers to deliver new features end to end. Write clean, maintainable, and well More ❯

Storage , Queues , and SQL/NoSQL databases to build scalable, event-driven systems. Design and optimise APIs that serve our mobile and web products, including partner integrations. Implement efficient RAG AI backend systems for introducing advanced LLM based features Collaborate with product managers, data engineers, and frontend developers to deliver new features end to end. Write clean, maintainable, and well More ❯

Storage , Queues , and SQL/NoSQL databases to build scalable, event-driven systems. Design and optimise APIs that serve our mobile and web products, including partner integrations. Implement efficient RAG AI backend systems for introducing advanced LLM based features Collaborate with product managers, data engineers, and frontend developers to deliver new features end to end. Write clean, maintainable, and well More ❯

/day (negotiable) About the Role: We are seeking a Senior Gen AI Engineer to develop and deploy advanced Generative AI products, including fine-tuning LLMs and implementing Graph RAG solutions. You will implement and optimize Gen AI agents for the Global Supply Chain, delivering scalable, secure, and cost-effective AI solutions. Key Responsibilities: Prototype and deploy Generative AI applications … for business objectives. Implement LLMs, Graph RAG, and AI/ML solutions in production environments. Develop automated processes (LLMOps) and CI/CD pipelines. Collaborate with cross-functional teams to integrate AI into business workflows. Ensure security, compliance, and AI governance standards. Educate IT and business teams on Gen AI capabilities. Required Experience & Skills: Higher degree (PhD preferred) in CS … Statistics, Physics, Bioinformatics, or related field. 5+ years of hands-on experience across AI domains: NLP, NLG, CV, ML, GenAI. Expertise in fine-tuning/training LLMs and Graph RAG solutions in production. Proficiency in cloud services and tools: Azure, Databricks, Azure ML, Vertex AI, Azure AI Services, Azure DevOps. Strong Python and LLM libraries experience: langchain, LangGraph, semantic kernel More ❯

/day (negotiable) About the Role: We are seeking a Senior Gen AI Engineer to develop and deploy advanced Generative AI products, including fine-tuning LLMs and implementing Graph RAG solutions. You will implement and optimize Gen AI agents for the Global Supply Chain, delivering scalable, secure, and cost-effective AI solutions. Key Responsibilities: Prototype and deploy Generative AI applications … for business objectives. Implement LLMs, Graph RAG, and AI/ML solutions in production environments. Develop automated processes (LLMOps) and CI/CD pipelines. Collaborate with cross-functional teams to integrate AI into business workflows. Ensure security, compliance, and AI governance standards. Educate IT and business teams on Gen AI capabilities. Required Experience & Skills: Higher degree (PhD preferred) in CS … Statistics, Physics, Bioinformatics, or related field. 5+ years of hands-on experience across AI domains: NLP, NLG, CV, ML, GenAI. Expertise in fine-tuning/training LLMs and Graph RAG solutions in production. Proficiency in cloud services and tools: Azure, Databricks, Azure ML, Vertex AI, Azure AI Services, Azure DevOps. Strong Python and LLM libraries experience: langchain, LangGraph, semantic kernel More ❯

/day (negotiable) About the Role: We are seeking a Senior Gen AI Engineer to develop and deploy advanced Generative AI products, including fine-tuning LLMs and implementing Graph RAG solutions. You will implement and optimize Gen AI agents for the Global Supply Chain, delivering scalable, secure, and cost-effective AI solutions. Key Responsibilities: Prototype and deploy Generative AI applications … for business objectives. Implement LLMs, Graph RAG, and AI/ML solutions in production environments. Develop automated processes (LLMOps) and CI/CD pipelines. Collaborate with cross-functional teams to integrate AI into business workflows. Ensure security, compliance, and AI governance standards. Educate IT and business teams on Gen AI capabilities. Required Experience & Skills: Higher degree (PhD preferred) in CS … Statistics, Physics, Bioinformatics, or related field. 5+ years of hands-on experience across AI domains: NLP, NLG, CV, ML, GenAI. Expertise in fine-tuning/training LLMs and Graph RAG solutions in production. Proficiency in cloud services and tools: Azure, Databricks, Azure ML, Vertex AI, Azure AI Services, Azure DevOps. Strong Python and LLM libraries experience: langchain, LangGraph, semantic kernel More ❯

/day (negotiable) About the Role: We are seeking a Senior Gen AI Engineer to develop and deploy advanced Generative AI products, including fine-tuning LLMs and implementing Graph RAG solutions. You will implement and optimize Gen AI agents for the Global Supply Chain, delivering scalable, secure, and cost-effective AI solutions. Key Responsibilities: Prototype and deploy Generative AI applications … for business objectives. Implement LLMs, Graph RAG, and AI/ML solutions in production environments. Develop automated processes (LLMOps) and CI/CD pipelines. Collaborate with cross-functional teams to integrate AI into business workflows. Ensure security, compliance, and AI governance standards. Educate IT and business teams on Gen AI capabilities. Required Experience & Skills: Higher degree (PhD preferred) in CS … Statistics, Physics, Bioinformatics, or related field. 5+ years of hands-on experience across AI domains: NLP, NLG, CV, ML, GenAI. Expertise in fine-tuning/training LLMs and Graph RAG solutions in production. Proficiency in cloud services and tools: Azure, Databricks, Azure ML, Vertex AI, Azure AI Services, Azure DevOps. Strong Python and LLM libraries experience: langchain, LangGraph, semantic kernel 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 ❯

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 ❯