326 to 350 of 365 Retrieval-Augmented Generation Jobs in London

/CDC) and entity resolution for 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: translate business problems into … TigerGraph, ArangoDB, OrientDB, or Stardog 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 to explain complex graph/ More ❯

/CDC) and entity resolution for 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: translate business problems into … TigerGraph, ArangoDB, OrientDB, or Stardog 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 to explain complex graph/ More ❯

/CDC) and entity resolution for 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: translate business problems into … TigerGraph, ArangoDB, OrientDB, or Stardog 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 to explain complex graph/ More ❯

Lead 100,000 + 20% Bonus Hybrid - 2 Days per Week in London 100,000 + 20% Bonus London - 2 days a week in office AWS, Python, Terraform, Kubernetes, RAG/GenAI interest Here at Burns Sheehan, we're exclusively partnered with a leading UK fintech that's transforming small business lending - processing billions in decisions annually. They've built … proven AWS cloud platform experience. Python scripting proficiency at platform engineer level but an understanding of software development lifecycle and production system ownership. Interest or experience in GenAI infrastructure - RAG, vector databases, LLM platforms, or agent frameworks. This role is NOT an ML Engineering position - you won't be training models or building LLMs. It's focused on the platform More ❯

Lead | £100,000 + 20% Bonus | Hybrid - 2 Days per Week in London 💰 £100,000 + 20% Bonus 📍 London - 2 days a week in office 🛠️ AWS, Python, Terraform, Kubernetes, RAG/GenAI interest Here at Burns Sheehan, we're exclusively partnered with a leading UK fintech that's transforming small business lending - processing billions in decisions annually. They've built … CloudFormation) and cloud-native development. Python scripting proficiency at platform engineer level but an understanding of software development lifecycle and production system ownership. Interest or experience in GenAI infrastructure - RAG, vector databases, LLM platforms, or agent frameworks. Strong communication skills and ability to translate technical decisions into business outcomes. This role is NOT an ML Engineering position - you won't More ❯

Lead | £100,000 + 20% Bonus | Hybrid - 2 Days per Week in London 💰 £100,000 + 20% Bonus 📍 London - 2 days a week in office 🛠️ AWS, Python, Terraform, Kubernetes, RAG/GenAI interest Here at Burns Sheehan, we're exclusively partnered with a leading UK fintech that's transforming small business lending - processing billions in decisions annually. They've built … CloudFormation) and cloud-native development. Python scripting proficiency at platform engineer level but an understanding of software development lifecycle and production system ownership. Interest or experience in GenAI infrastructure - RAG, vector databases, LLM platforms, or agent frameworks. Strong communication skills and ability to translate technical decisions into business outcomes. This role is NOT an ML Engineering position - you won't More ❯

Do you want to build the infrastructure powering the next generation of AI agents? Have you scaled backend systems that drive automation at speed? Ready to join a profitable AI startup transforming how industries deploy technology? A profitable, fast-growing AI company is building the “roads” for AI agents — providing the infrastructure that lets businesses deploy and integrate …/LLM components into production systems. Role Breakdown: 50% Backend Engineering: FastAPI, Flask, Node.js, CI/CD 30% Data Engineering: ETL, DBT, Airflow 20% AI/LLM Integration: LangChain, RAG pipelines, orchestration Key Responsibilities: Design and build backend services to support AI agent deployment Develop scalable data pipelines and integration layers Implement AI/LLM-powered features with LangChain and … of Front-End, and adoption engineers Reporting Line: CTO Visa: Cannot sponsor Ideal Profile: 5–8 years’ experience in backend or data engineering (Python) Exposure to AI/LLMs, RAG, or personal AI side projects Experience in startups or scale-ups where you’ve helped build or grow systems Solid education and strong coding fundamentals Comfortable working in a small More ❯

Do you want to build the infrastructure powering the next generation of AI agents? Have you scaled backend systems that drive automation at speed? Ready to join a profitable AI startup transforming how industries deploy technology? A profitable, fast-growing AI company is building the “roads” for AI agents — providing the infrastructure that lets businesses deploy and integrate …/LLM components into production systems. Role Breakdown: 50% Backend Engineering: FastAPI, Flask, Node.js, CI/CD 30% Data Engineering: ETL, DBT, Airflow 20% AI/LLM Integration: LangChain, RAG pipelines, orchestration Key Responsibilities: Design and build backend services to support AI agent deployment Develop scalable data pipelines and integration layers Implement AI/LLM-powered features with LangChain and … of Front-End, and adoption engineers Reporting Line: CTO Visa: Cannot sponsor Ideal Profile: 5–8 years’ experience in backend or data engineering (Python) Exposure to AI/LLMs, RAG, or personal AI side projects Experience in startups or scale-ups where you’ve helped build or grow systems Solid education and strong coding fundamentals Comfortable working in a small More ❯

Do you want to build the infrastructure powering the next generation of AI agents? Have you scaled backend systems that drive automation at speed? Ready to join a profitable AI startup transforming how industries deploy technology? A profitable, fast-growing AI company is building the “roads” for AI agents — providing the infrastructure that lets businesses deploy and integrate …/LLM components into production systems. Role Breakdown: 50% Backend Engineering: FastAPI, Flask, Node.js, CI/CD 30% Data Engineering: ETL, DBT, Airflow 20% AI/LLM Integration: LangChain, RAG pipelines, orchestration Key Responsibilities: Design and build backend services to support AI agent deployment Develop scalable data pipelines and integration layers Implement AI/LLM-powered features with LangChain and … of Front-End, and adoption engineers Reporting Line: CTO Visa: Cannot sponsor Ideal Profile: 5–8 years’ experience in backend or data engineering (Python) Exposure to AI/LLMs, RAG, or personal AI side projects Experience in startups or scale-ups where you’ve helped build or grow systems Solid education and strong coding fundamentals Comfortable working in a small More ❯

Do you want to build the infrastructure powering the next generation of AI agents? Have you scaled backend systems that drive automation at speed? Ready to join a profitable AI startup transforming how industries deploy technology? A profitable, fast-growing AI company is building the “roads” for AI agents — providing the infrastructure that lets businesses deploy and integrate …/LLM components into production systems. Role Breakdown: 50% Backend Engineering: FastAPI, Flask, Node.js, CI/CD 30% Data Engineering: ETL, DBT, Airflow 20% AI/LLM Integration: LangChain, RAG pipelines, orchestration Key Responsibilities: Design and build backend services to support AI agent deployment Develop scalable data pipelines and integration layers Implement AI/LLM-powered features with LangChain and … of Front-End, and adoption engineers Reporting Line: CTO Visa: Cannot sponsor Ideal Profile: 5–8 years’ experience in backend or data engineering (Python) Exposure to AI/LLMs, RAG, or personal AI side projects Experience in startups or scale-ups where you’ve helped build or grow systems Solid education and strong coding fundamentals Comfortable working in a small More ❯

Engineer , you’ll take ownership of core backend systems powering an advanced AI platform that integrates production-ready LLMs and agentic systems. You’ll architect scalable backend services, build RAG pipelines, and integrate AI components into distributed systems that enable real-world, production-scale AI deployment . 🔧 What You’ll Do Architect and develop backend systems (Python, FastAPI, Flask, NodeJS … Design and implement RAG pipelines (LangChain, Qdrant, embeddings) Build ETL & CI/CD workflows (Airflow, dbt, MLFlow) Integrate AI/LLM components into backend services Ensure reliability, scalability, and maintainability across systems Collaborate with a small, elite team of engineers and AI researchers 💼 About You 4+ years of backend experience (Python, distributed systems, async APIs) Proven experience integrating AI or More ❯

Engineer , you’ll take ownership of core backend systems powering an advanced AI platform that integrates production-ready LLMs and agentic systems. You’ll architect scalable backend services, build RAG pipelines, and integrate AI components into distributed systems that enable real-world, production-scale AI deployment . 🔧 What You’ll Do Architect and develop backend systems (Python, FastAPI, Flask, NodeJS … Design and implement RAG pipelines (LangChain, Qdrant, embeddings) Build ETL & CI/CD workflows (Airflow, dbt, MLFlow) Integrate AI/LLM components into backend services Ensure reliability, scalability, and maintainability across systems Collaborate with a small, elite team of engineers and AI researchers 💼 About You 4+ years of backend experience (Python, distributed systems, async APIs) Proven experience integrating AI or More ❯

Engineer , you’ll take ownership of core backend systems powering an advanced AI platform that integrates production-ready LLMs and agentic systems. You’ll architect scalable backend services, build RAG pipelines, and integrate AI components into distributed systems that enable real-world, production-scale AI deployment . 🔧 What You’ll Do Architect and develop backend systems (Python, FastAPI, Flask, NodeJS … Design and implement RAG pipelines (LangChain, Qdrant, embeddings) Build ETL & CI/CD workflows (Airflow, dbt, MLFlow) Integrate AI/LLM components into backend services Ensure reliability, scalability, and maintainability across systems Collaborate with a small, elite team of engineers and AI researchers 💼 About You 4+ years of backend experience (Python, distributed systems, async APIs) Proven experience integrating AI or More ❯

Engineer , you’ll take ownership of core backend systems powering an advanced AI platform that integrates production-ready LLMs and agentic systems. You’ll architect scalable backend services, build RAG pipelines, and integrate AI components into distributed systems that enable real-world, production-scale AI deployment . 🔧 What You’ll Do Architect and develop backend systems (Python, FastAPI, Flask, NodeJS … Design and implement RAG pipelines (LangChain, Qdrant, embeddings) Build ETL & CI/CD workflows (Airflow, dbt, MLFlow) Integrate AI/LLM components into backend services Ensure reliability, scalability, and maintainability across systems Collaborate with a small, elite team of engineers and AI researchers 💼 About You 4+ years of backend experience (Python, distributed systems, async APIs) Proven experience integrating AI or More ❯

Do 🔧 Design and implement end-to-end data pipelines linking core platforms (CRM → data lake → AI systems) Architect schemas and transformation layers optimized for analytics, automation, and AI workflows (RAG/internal copilots) Build Python and API integrations , using low-code/no-code tools (Zapier, Make, Matillion) where it speeds things up Prototype internal automations and AI-driven tools … than waiting for perfect architecture ✨ Nice-to-Haves: Experience with CRM platforms (Zoho, HubSpot, Salesforce) and scripting Familiarity with Snowflake or modern cloud data warehouses Awareness of LLM APIs, RAG concepts, or AI workflow orchestration Who You Are 🎯 Early-career to mid-career (2–6 years experience), eager for ownership and growth A pragmatic builder who enjoys wiring systems together … data flow end-to-end Hands-on, execution-focused, and comfortable shipping fast rather than waiting for perfect architecture Curious about AI and automation, with experience or interest in RAG, internal copilots, or AI workflows Able to communicate clearly with technical and non-technical stakeholders 📩 Interested? If you’re a Python + data + integration engineer who enjoys building AI More ❯

Do 🔧 Design and implement end-to-end data pipelines linking core platforms (CRM → data lake → AI systems) Architect schemas and transformation layers optimized for analytics, automation, and AI workflows (RAG/internal copilots) Build Python and API integrations , using low-code/no-code tools (Zapier, Make, Matillion) where it speeds things up Prototype internal automations and AI-driven tools … than waiting for perfect architecture ✨ Nice-to-Haves: Experience with CRM platforms (Zoho, HubSpot, Salesforce) and scripting Familiarity with Snowflake or modern cloud data warehouses Awareness of LLM APIs, RAG concepts, or AI workflow orchestration Who You Are 🎯 Early-career to mid-career (2–6 years experience), eager for ownership and growth A pragmatic builder who enjoys wiring systems together … data flow end-to-end Hands-on, execution-focused, and comfortable shipping fast rather than waiting for perfect architecture Curious about AI and automation, with experience or interest in RAG, internal copilots, or AI workflows Able to communicate clearly with technical and non-technical stakeholders 📩 Interested? If you’re a Python + data + integration engineer who enjoys building AI More ❯

Do 🔧 Design and implement end-to-end data pipelines linking core platforms (CRM → data lake → AI systems) Architect schemas and transformation layers optimized for analytics, automation, and AI workflows (RAG/internal copilots) Build Python and API integrations , using low-code/no-code tools (Zapier, Make, Matillion) where it speeds things up Prototype internal automations and AI-driven tools … than waiting for perfect architecture ✨ Nice-to-Haves: Experience with CRM platforms (Zoho, HubSpot, Salesforce) and scripting Familiarity with Snowflake or modern cloud data warehouses Awareness of LLM APIs, RAG concepts, or AI workflow orchestration Who You Are 🎯 Early-career to mid-career (2–6 years experience), eager for ownership and growth A pragmatic builder who enjoys wiring systems together … data flow end-to-end Hands-on, execution-focused, and comfortable shipping fast rather than waiting for perfect architecture Curious about AI and automation, with experience or interest in RAG, internal copilots, or AI workflows Able to communicate clearly with technical and non-technical stakeholders 📩 Interested? If you’re a Python + data + integration engineer who enjoys building AI More ❯

Do 🔧 Design and implement end-to-end data pipelines linking core platforms (CRM → data lake → AI systems) Architect schemas and transformation layers optimized for analytics, automation, and AI workflows (RAG/internal copilots) Build Python and API integrations , using low-code/no-code tools (Zapier, Make, Matillion) where it speeds things up Prototype internal automations and AI-driven tools … than waiting for perfect architecture ✨ Nice-to-Haves: Experience with CRM platforms (Zoho, HubSpot, Salesforce) and scripting Familiarity with Snowflake or modern cloud data warehouses Awareness of LLM APIs, RAG concepts, or AI workflow orchestration Who You Are 🎯 Early-career to mid-career (2–6 years experience), eager for ownership and growth A pragmatic builder who enjoys wiring systems together … data flow end-to-end Hands-on, execution-focused, and comfortable shipping fast rather than waiting for perfect architecture Curious about AI and automation, with experience or interest in RAG, internal copilots, or AI workflows Able to communicate clearly with technical and non-technical stakeholders 📩 Interested? If you’re a Python + data + integration engineer who enjoys building AI More ❯

Do you want to build the infrastructure powering the next generation of AI agents? Have you scaled backend systems that drive automation at speed? Ready to join a profitable AI startup transforming how industries deploy technology? A profitable, fast-growing AI company is building the roads for AI agents providing the infrastructure that lets businesses deploy and integrate … founding group including CTO, Head of Front-End, and adoption engineers Visa: Cannot sponsor 5 8 years experience in backend or data engineering (Python) Exposure to AI/LLMs, RAG, or personal AI side projects Experience in startups or scale-ups where you ve helped build or grow systems Solid education and strong coding fundamentals This is an opportunity to More ❯

and applied AI , taking ownership of projects end-to-end, from experimentation to deployment. If you What You’ll Do Design, implement, and ship production-grade LLM applications (prompting, RAG, evaluation, deployment). Develop and refine AI pipelines and retrieval systems using tools like LangChain, LangGraph, or custom frameworks. Own model evaluation frameworks to ensure quality, factuality, and …/ML applications. Proven track record of shipping AI products into production (not just research or prototypes). Preferred tech stack - TypeScript, React, LangChain, and LLM orchestration. Experience with RAG systems , vector databases (e.g. Pinecone, PGVector, Weaviate), and model evaluation . Comfortable working in a fast-paced startup environment with a high degree of autonomy. Exposure to agentic systems, prompt More ❯

and applied AI , taking ownership of projects end-to-end, from experimentation to deployment. If you What You’ll Do Design, implement, and ship production-grade LLM applications (prompting, RAG, evaluation, deployment). Develop and refine AI pipelines and retrieval systems using tools like LangChain, LangGraph, or custom frameworks. Own model evaluation frameworks to ensure quality, factuality, and …/ML applications. Proven track record of shipping AI products into production (not just research or prototypes). Preferred tech stack - TypeScript, React, LangChain, and LLM orchestration. Experience with RAG systems , vector databases (e.g. Pinecone, PGVector, Weaviate), and model evaluation . Comfortable working in a fast-paced startup environment with a high degree of autonomy. Exposure to agentic systems, prompt More ❯

and applied AI , taking ownership of projects end-to-end, from experimentation to deployment. If you What You’ll Do Design, implement, and ship production-grade LLM applications (prompting, RAG, evaluation, deployment). Develop and refine AI pipelines and retrieval systems using tools like LangChain, LangGraph, or custom frameworks. Own model evaluation frameworks to ensure quality, factuality, and …/ML applications. Proven track record of shipping AI products into production (not just research or prototypes). Preferred tech stack - TypeScript, React, LangChain, and LLM orchestration. Experience with RAG systems , vector databases (e.g. Pinecone, PGVector, Weaviate), and model evaluation . Comfortable working in a fast-paced startup environment with a high degree of autonomy. Exposure to agentic systems, prompt More ❯

and applied AI , taking ownership of projects end-to-end, from experimentation to deployment. If you What You’ll Do Design, implement, and ship production-grade LLM applications (prompting, RAG, evaluation, deployment). Develop and refine AI pipelines and retrieval systems using tools like LangChain, LangGraph, or custom frameworks. Own model evaluation frameworks to ensure quality, factuality, and …/ML applications. Proven track record of shipping AI products into production (not just research or prototypes). Preferred tech stack - TypeScript, React, LangChain, and LLM orchestration. Experience with RAG systems , vector databases (e.g. Pinecone, PGVector, Weaviate), and model evaluation . Comfortable working in a fast-paced startup environment with a high degree of autonomy. Exposure to agentic systems, prompt More ❯

user-focused AI services across our business. What You’ll Do Design and implement a comprehensive AI testing and evaluation framework for all AI solutions, including LLM-based tools, RAG systems, and third-party platforms. Define and document quality standards for semantic accuracy, factual consistency, bias, tone, and relevance. Develop reusable testing templates, data sets, and evaluation methods that can … LLM behaviour (accuracy, hallucination, bias, tone, etc.). Familiarity with tools like Trulens, HumanLoop, PromptLayer, or similar; experience designing QA approaches for GenAI environments. Knowledge of modern AI architectures (RAG pipelines, embeddings, API integrations such as OpenAI, Azure OpenAI, Anthropic). Experience designing and implementing structured test regimes in fast-evolving contexts. Excellent communication and facilitation skills, engaging both technical More ❯

user-focused AI services across our business. What You’ll Do Design and implement a comprehensive AI testing and evaluation framework for all AI solutions, including LLM-based tools, RAG systems, and third-party platforms. Define and document quality standards for semantic accuracy, factual consistency, bias, tone, and relevance. Develop reusable testing templates, data sets, and evaluation methods that can … LLM behaviour (accuracy, hallucination, bias, tone, etc.). Familiarity with tools like Trulens, HumanLoop, PromptLayer, or similar; experience designing QA approaches for GenAI environments. Knowledge of modern AI architectures (RAG pipelines, embeddings, API integrations such as OpenAI, Azure OpenAI, Anthropic). Experience designing and implementing structured test regimes in fast-evolving contexts. Excellent communication and facilitation skills, engaging both technical More ❯