276 to 300 of 365 Retrieval-Augmented Generation Jobs in London

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 ❯

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 ❯

over 175,000 new developers signing up to use MongoDB every month, it's no wonder that leading organizations, like Samsung and Toyota, trust MongoDB to build next-generation, AI-powered applications. We are looking for passionate technologists to join our Pre-Sales organization to ensure that our growth is grounded and guided by strong technical alignment with … communicating its business value to the relevant stakeholders Sales Partnership: Collaborate with the sales team to drive account success through account planning, opportunity prioritization/qualification and pipeline generation strategy, while taking ownership of the technical aspects (including but not limited to technical discovery, demos, proof of value, presentations, sizing and documentation) Demand Generation: Proactively generate … Enhance your skills with partner and complementary technologies such as Apache Kafka and Kubernetes Design Patterns and Methodologies: Embrace best practices in microservices, DevOps, cloud, and security Cutting Edge RAG and AI Architectures: Help customers on their generative AI journeys and working with industry leading partners in the space Sales Techniques and Soft Skills: Effective Communication: Master presentations, demonstrations, and 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 ❯

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 ❯

AI capabilities at scale. We’re hiring an experienced, hands-on Machine Learning Engineer to architect and deliver production-grade AI system — with a strong focus on MCP, RAG, and real-world deployment . This project is a green field build out of AI capabilities. We are starting with RAG use cases as a low bar, but are targeting … the VP of Engineering Architect, build and ship advanced AI/ML & Generative AI solutions — scalable, secure, production-ready Design data ingestion pipelines, integrate vector databases and retrieval-augmented systems Ship models via APIs, containers, or cloud-native services Own engineering excellence — Git, CI/CD, automated ML testing, IaC Influence technical direction and mentor other … translate AI strategy into measurable business outcomes What you bring Expert Python — LangChain, Semantic Kernel, PyTorch, TensorFlow Hands-on cloud delivery — Azure/AWS, Terraform, ECS Proven experience building RAG/MCP architectures 5+ years in applied ML or AI engineering roles Send us your profile now for immediate consideration. November start. More ❯

AI capabilities at scale. We’re hiring an experienced, hands-on Machine Learning Engineer to architect and deliver production-grade AI system — with a strong focus on MCP, RAG, and real-world deployment . This project is a green field build out of AI capabilities. We are starting with RAG use cases as a low bar, but are targeting … the VP of Engineering Architect, build and ship advanced AI/ML & Generative AI solutions — scalable, secure, production-ready Design data ingestion pipelines, integrate vector databases and retrieval-augmented systems Ship models via APIs, containers, or cloud-native services Own engineering excellence — Git, CI/CD, automated ML testing, IaC Influence technical direction and mentor other … translate AI strategy into measurable business outcomes What you bring Expert Python — LangChain, Semantic Kernel, PyTorch, TensorFlow Hands-on cloud delivery — Azure/AWS, Terraform, ECS Proven experience building RAG/MCP architectures 5+ years in applied ML or AI engineering roles Send us your profile now for immediate consideration. November start. More ❯

and analytics solutions aligned with the organisations Data & AI strategy. End-to-end development of AI/ML solutions. CI/CD, model monitoring, retraining. Generative AI features: embeddings, RAG, AI agents. 24 years in production-level AI/ML delivery. Legal/professional services experience is a plus. AI/ML frameworks: Azure (preferred), AWS, GCP. MLOps: CI/… CD, model lifecycle, monitoring. Generative AI: LLMs, RAG, chat agents. Data engineering alignment: Strong coding, communication, and collaboration skills. 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 ❯

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 ❯

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 ❯

their product, data, and software teams to build adaptive solutions that enhance productivity, automate workflows, and enable smarter business processes. This is an opportunity to shape how next-generation AI is applied in a fast-moving SME environment—balancing hands-on technical work with strategic innovation. Key Responsibilities Design, build, and deploy AI agents using frameworks such as … tools. Familiarity with APIs, databases, and cloud infrastructure (AWS, Azure, or GCP). Desirable: Experience in small, agile teams or start-up/SME environments. Knowledge of vector databases, RAG systems, or AI orchestration platforms. Interest in autonomous systems, cognitive architectures, or workflow automation. More ❯

their product, data, and software teams to build adaptive solutions that enhance productivity, automate workflows, and enable smarter business processes. This is an opportunity to shape how next-generation AI is applied in a fast-moving SME environment—balancing hands-on technical work with strategic innovation. Key Responsibilities Design, build, and deploy AI agents using frameworks such as … tools. Familiarity with APIs, databases, and cloud infrastructure (AWS, Azure, or GCP). Desirable: Experience in small, agile teams or start-up/SME environments. Knowledge of vector databases, RAG systems, or AI orchestration platforms. Interest in autonomous systems, cognitive architectures, or workflow automation. More ❯

their product, data, and software teams to build adaptive solutions that enhance productivity, automate workflows, and enable smarter business processes. This is an opportunity to shape how next-generation AI is applied in a fast-moving SME environment—balancing hands-on technical work with strategic innovation. Key Responsibilities Design, build, and deploy AI agents using frameworks such as … tools. Familiarity with APIs, databases, and cloud infrastructure (AWS, Azure, or GCP). Desirable: Experience in small, agile teams or start-up/SME environments. Knowledge of vector databases, RAG systems, or AI orchestration platforms. Interest in autonomous systems, cognitive architectures, or workflow automation. More ❯

Full Stack AI Software Engineer - Full Remote UK - £90,000 + Equity This role requires a software engineer with experience in implementing RAG pipelines and Vector Search (and hybrid AI searches, preferably). The client I am working with is an AI focused start-up backed by a £1.7M pre-seed investment. They are on a mission to streamline the … an early stage. What you'll work on: Backend APIs (Python/FastAPI): Build and maintain secure, high-performance services that drive AI features and data access at scale. RAG & vector search: Design and improve retrieval pipelines (embeddings, chunking, hybrid search, ranking, feedback loops), owning schema design, latency, and relevance across vector databases. LLM integration: Connect and orchestrate … AI development. Requirements: A motivated, hands-on engineer with an ownership mindset, strong communication skills, and a collaborative approach. 5+ years’ experience in full-stack development. Strong background in RAG systems , vector databases (pgvector, FAISS, Weaviate, Elasticsearch k-NN), embeddings, and hybrid search methods. Practical knowledge of chunking strategies, indexing, precision/recall trade-offs, reranking, and evaluation techniques. Proficient More ❯

Technical Leadership Define and lead the AI & Data Science vision and roadmap , aligned with business priorities. Provide technical oversight for AI initiatives across domains: Generative AI & LLMs (fine-tuning, RAG pipelines, multi-agent systems). Predictive Analytics & Time-Series Modeling . Computer Vision & Multimodal AI . Reinforcement Learning & Optimization . Knowledge Engineering & Semantic Search . Edge AI & Real-Time AI … and client engagements . Required Qualifications Significant experience in AI/ML, including experience in a technical leadership or team lead role . Strong knowledge (architectural & practical) of: LLMs, RAG, and AI Agents . Predictive analytics & time-series forecasting . Computer vision, multimodal learning, and geospatial AI . Reinforcement learning and optimization techniques . MLOps practices & data pipelines . Ability More ❯