201 to 225 of 260 Retrieval-Augmented Generation Jobs in London

powered Predictive Intelligence Platform for corporates and financial institutions. Their technology connects market events, client data, and emerging opportunities through advanced agentic AI and RAG-based systems, helping financial institutions anticipate client needs before they arise. They have built a live MVP in record time, with enterprise client demos underway … lead the design and productionisation of the company’s core AI systems. You will architect, implement, evaluate, and scale RAG pipelines, agentic workflows, and LLM-based intelligence frameworks, driving real-world impact across financial markets. The role is approximately 80% hands-on and 20% strategic, covering Python engineering, system architecture ...

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 … 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 ...

controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures It Would Be Great If You Also Had Experience In Some Of These, But If Not Well Help You With Them Experience with advanced … techniques: agents, tool use, and agentic workflows Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications Experience with feature stores (Feast, AWS Feature Store) Experience with containerisation (Docker) and orchestration (Kubernetes, ECS) Familiarity with Infrastructure as Code (Terraform, CloudFormation) Experience with data processing frameworks (Spark, Dask) for large-scale ...

controls • Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) • Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures It Would Be Great If You Also Had Experience In Some Of These, But If Not We’ll Help You With Them • Experience with … advanced LLM techniques: agents, tool use, and agentic workflows • Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications • Experience with feature stores (Feast, AWS Feature Store) • Experience with containerisation (Docker) and orchestration (Kubernetes, ECS) • Familiarity with Infrastructure as Code (Terraform, CloudFormation) • Experience with data processing frameworks (Spark, Dask ...

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 … 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. ...

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 … 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. ...

precision of AI engineering with the ambition of a fintech disruptor. That’s what this role offers. I’m working with a next-generation technology company that’s fusing agentic AI with financial innovation to create intelligent systems that don’t just automate - they think, adapt, and transform … experience building GenAI systems in production environments. Strong Python skills and a GitHub portfolio showcasing MLE or GenAI projects. Expertise in LLMs, prompt engineering, RAG, vector databases, and agentic frameworks (LangChain, LlamaIndex, DSPy, etc.). Ability to break down complex business domains into computational workflows. Excellent communication skills and comfort ...

precision of AI engineering with the ambition of a fintech disruptor. That’s what this role offers. I’m working with a next-generation technology company that’s fusing agentic AI with financial innovation to create intelligent systems that don’t just automate - they think, adapt, and transform … experience building GenAI systems in production environments. Strong Python skills and a GitHub portfolio showcasing MLE or GenAI projects. Expertise in LLMs, prompt engineering, RAG, vector databases, and agentic frameworks (LangChain, LlamaIndex, DSPy, etc.). Ability to break down complex business domains into computational workflows. Excellent communication skills and comfort ...

from concept through to secure, scalable production deployment. You’ll work across engineering, commercial, and operational teams to develop GenAI tools including retrieval-augmented systems, intelligent assistants, and workflow automation. Your work will be central to embedding GenAI into enterprise platforms, unlocking measurable business outcomes while … ensuring maintainability, security, and compliance. Key Responsibilities Lead the design and delivery of production-grade GenAI solutions using LLMs, RAG, and vector search, optimising prompts, context, and retrieval for accuracy and performance. Architect and implement GenAI services integrated with enterprise systems and cloud platforms, ensuring scalability, security ...

from concept through to secure, scalable production deployment. You’ll work across engineering, commercial, and operational teams to develop GenAI tools including retrieval-augmented systems, intelligent assistants, and workflow automation. Your work will be central to embedding GenAI into enterprise platforms, unlocking measurable business outcomes while … ensuring maintainability, security, and compliance. Key Responsibilities Lead the design and delivery of production-grade GenAI solutions using LLMs, RAG, and vector search, optimising prompts, context, and retrieval for accuracy and performance. Architect and implement GenAI services integrated with enterprise systems and cloud platforms, ensuring scalability, security ...

additional AI Engineer join the existing team on a expanding project. This role will be shipping production-grade GenAI features (e.g., retrieval-augmented generation, assistants, summarisation) that are safe, reliable, and measurable. This role is based in a Local office. This role will … guardrail incidents, drift, telemetry dashboards Required Skills & Experience: Python for application glue; Fast API for inference/middleware services. LLM integration patterns (prompt engineering, RAG, tool-use/agents, function calling). Evaluation & safety: automated prompt/response evals, LLM-as-a-judge, red-teaming, content filters, guardrails. LLMOps practices ...

orchestration, prompt frameworks, and evaluation loops Build multi-agent systems (planning, tool use, safety constraints, monitoring) Implement retrieval and vector-based architectures (RAG, embeddings, semantic workflows) Apply ontology and knowledge-modelling concepts for more precise reasoning Integrate APIs, tools, and enterprise systems Set the technical direction for your … practices Influence internal standards and architectures Experience Needed 6–8+ years in software, AI, or applied data engineering Strong hands-on experience with LLMs, RAG, vector stores, and embeddings Experience building or orchestrating multi-agent systems Strong Python skills and ability to ship production-grade code Experience with at least ...

orchestration, prompt frameworks, and evaluation loops Build multi-agent systems (planning, tool use, safety constraints, monitoring) Implement retrieval and vector-based architectures (RAG, embeddings, semantic workflows) Apply ontology and knowledge-modelling concepts for more precise reasoning Integrate APIs, tools, and enterprise systems Set the technical direction for your … practices Influence internal standards and architectures Experience Needed 6–8+ years in software, AI, or applied data engineering Strong hands-on experience with LLMs, RAG, vector stores, and embeddings Experience building or orchestrating multi-agent systems Strong Python skills and ability to ship production-grade code Experience with at least ...

OpenAI environment Build Prof. T v0.1 — our AI tutor trained on curriculum, assessments, and teaching materials Create retrieval and vector-based pipelines (RAG) for structured learning content Build internal tools for academics to upload, review, and refine materials Work with leadership to define our long-term AI roadmap … entire institution. What we’re looking for Essential Experience with Azure OpenAI, OpenAI, LangChain, or similar frameworks Strong Python engineering skills Practical experience building RAG systems, embeddings, vector stores Comfort with cloud architecture (Azure preferred) Ability to move fast, prototype, and ship Experience building MVPs, internal tools, or early-stage ...

OpenAI environment Build Prof. T v0.1 — our AI tutor trained on curriculum, assessments, and teaching materials Create retrieval and vector-based pipelines (RAG) for structured learning content Build internal tools for academics to upload, review, and refine materials Work with leadership to define our long-term AI roadmap … entire institution. What we’re looking for Essential Experience with Azure OpenAI, OpenAI, LangChain, or similar frameworks Strong Python engineering skills Practical experience building RAG systems, embeddings, vector stores Comfort with cloud architecture (Azure preferred) Ability to move fast, prototype, and ship Experience building MVPs, internal tools, or early-stage ...

NetMind.ai, we’re building the next-generation AI/ML platform powered by a global decentralized GPU infrastructure. Our mission is to deliver the simplest and most accessible generative AI solutions on the market and democratize access to AI technology globally. Our AI services range from inference model … within days (or hours) to support client pitches. AI Stack Integration: Utilize Claude Code Agent, Google Gemini, and OpenAI APIs to implement features like RAG, document analysis, and automated workflows. Full-Stack Lite: Use Python and Streamlit to create clean, interactive, and client-ready user interfaces. Prompt Engineering: Design ...

NetMind.ai, we’re building the next-generation AI/ML platform powered by a global decentralized GPU infrastructure. Our mission is to deliver the simplest and most accessible generative AI solutions on the market and democratize access to AI technology globally. Our AI services range from inference model … within days (or hours) to support client pitches. AI Stack Integration: Utilize Claude Code Agent, Google Gemini, and OpenAI APIs to implement features like RAG, document analysis, and automated workflows. Full-Stack Lite: Use Python and Streamlit to create clean, interactive, and client-ready user interfaces. Prompt Engineering: Design ...

capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge. We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People … Langchain, AutoML, OCR, STT, feature stores, vector DB Implementation of AI/ML architectural patterns and best practices e.g. data drift detection, experimentation tracking, RAG, deployment models Building and using cloud-based solutions (networking, security, storage, monitoring, scaling, DR/HA) on one or more cloud platforms SW Engineering ...

capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge. We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People … Langchain, AutoML, OCR, STT, feature stores, vector DB Implementation of AI/ML architectural patterns and best practices e.g. data drift detection, experimentation tracking, RAG, deployment models Building and using cloud-based solutions (networking, security, storage, monitoring, scaling, DR/HA) on one or more cloud platforms SW Engineering ...

want to shape how LLMs are deployed at scale in a real business? Have you built RAG or agentic systems that moved beyond experimentation? Are you motivated by measurable customer and commercial impact, not demos? A private-equity-backed consumer services business is scaling its Data Science & AI capability … year transformation. Following an award-winning data programme, the company now has an established AI function and is investing further in LLM-powered assistants, RAG pipelines, voice/chat intelligence and early agentic workflows across both customer-facing and internal products. This Senior AI Engineer role is a hands ...

want to shape how LLMs are deployed at scale in a real business? Have you built RAG or agentic systems that moved beyond experimentation? Are you motivated by measurable customer and commercial impact, not demos? A private-equity-backed consumer services business is scaling its Data Science & AI capability … year transformation. Following an award-winning data programme, the company now has an established AI function and is investing further in LLM-powered assistants, RAG pipelines, voice/chat intelligence and early agentic workflows across both customer-facing and internal products. This Senior AI Engineer role is a hands ...

graph population Author complex queries (Cypher, GSQL, AQL, SPARQL etc. depending on stack) Integrate knowledge graph retrieval & reasoning into LLM/RAG/GraphRAG systems Develop and evaluate graph ML/embedding models (link prediction, anomaly detection) Optimize graph performance, scaling, and query efficiency Liaise with client stakeholders … Proficiency in query languages (Cypher, GSQL, AQL, SPARQL, etc.) Strong background in pipelines, ETL, and entity resolution Exposure to integrating KG + LLM or RAG architectures Experience with graph algorithms, embeddings, or GNNs Cloud & production engineering literacy (AWS/Azure/GCP, containerization, CI/CD) Excellent communication skills — able ...

graph population Author complex queries (Cypher, GSQL, AQL, SPARQL etc. depending on stack) Integrate knowledge graph retrieval & reasoning into LLM/RAG/GraphRAG systems Develop and evaluate graph ML/embedding models (link prediction, anomaly detection) Optimize graph performance, scaling, and query efficiency Liaise with client stakeholders … Proficiency in query languages (Cypher, GSQL, AQL, SPARQL, etc.) Strong background in pipelines, ETL, and entity resolution Exposure to integrating KG + LLM or RAG architectures Experience with graph algorithms, embeddings, or GNNs Cloud & production engineering literacy (AWS/Azure/GCP, containerization, CI/CD) Excellent communication skills — able ...

products at scale. Sitting at the core of AI delivery, you will design, build, and operate the runtime, infrastructure, and operational layers supporting RAG pipelines, LLM orchestration, vector search, and evaluation workflows across AWS and Databricks. Working closely with senior AI engineers and product teams, you'll ensure AI systems … With further scope of responsibilities detailed below: Own and evolve the AI platform powering conversational assistants and generative AI products. Build, operate, and optimise RAG and LLM-backed services, improving latency, reliability, and cost. Design and run cloud-native AI services across AWS and Databricks, including ingestion and embedding pipelines. ...

products at scale. Sitting at the core of AI delivery, you will design, build, and operate the runtime, infrastructure, and operational layers supporting RAG pipelines, LLM orchestration, vector search, and evaluation workflows across AWS and Databricks. Working closely with senior AI engineers and product teams, you'll ensure AI systems … With further scope of responsibilities detailed below: Own and evolve the AI platform powering conversational assistants and generative AI products. Build, operate, and optimise RAG and LLM-backed services, improving latency, reliability, and cost. Design and run cloud-native AI services across AWS and Databricks, including ingestion and embedding pipelines. ...