126 to 150 of 358 Retrieval-Augmented Generation Jobs in London

AI/LLM Engineer/Architect (Contract) - RAG … Implementation| London (mostly remote) - Outside IR35 We're looking for a highly skilled AI/LLM Engineer/Architect to lead the implementation of Retrieval Augmented Generation (RAG) solutions for a major client project in London. This is a hands-on contract role for someone who can build from the ground up - shaping the … steer the organisation's AI stack, define best practices, and ensure the delivery of scalable, cost-effective solutions. What You'll Do • Lead the design, build, and deployment of RAG solutions • Drive Agentic development and intelligent automation • Provide guidance on AI architecture and technology strategy • Build and deploy scalable machine learning applications on AWS • Apply ML Ops tooling and workflows More ❯

AI/LLM Engineer/Architect (Contract) - RAG … Implementation| London (mostly remote) - Outside IR35 We're looking for a highly skilled AI/LLM Engineer/Architect to lead the implementation of Retrieval Augmented Generation (RAG) solutions for a major client project in London. This is a hands-on contract role for someone who can build from the ground up - shaping the … steer the organisation's AI stack, define best practices, and ensure the delivery of scalable, cost-effective solutions. What You'll Do • Lead the design, build, and deployment of RAG solutions • Drive Agentic development and intelligent automation • Provide guidance on AI architecture and technology strategy • Build and deploy scalable machine learning applications on AWS • Apply ML Ops tooling and workflows More ❯

AI/LLM Engineer/Architect (Contract) - RAG … Implementation| London (mostly remote) - Outside IR35 We're looking for a highly skilled AI/LLM Engineer/Architect to lead the implementation of Retrieval Augmented Generation (RAG) solutions for a major client project in London. This is a hands-on contract role for someone who can build from the ground up - shaping the … steer the organisation's AI stack, define best practices, and ensure the delivery of scalable, cost-effective solutions. What You'll Do • Lead the design, build, and deployment of RAG solutions • Drive Agentic development and intelligent automation • Provide guidance on AI architecture and technology strategy • Build and deploy scalable machine learning applications on AWS • Apply ML Ops tooling and workflows More ❯

AI/LLM Engineer/Architect (Contract) - RAG … Implementation| London (mostly remote) - Outside IR35 We're looking for a highly skilled AI/LLM Engineer/Architect to lead the implementation of Retrieval Augmented Generation (RAG) solutions for a major client project in London. This is a hands-on contract role for someone who can build from the ground up - shaping the … steer the organisation's AI stack, define best practices, and ensure the delivery of scalable, cost-effective solutions. What You'll Do • Lead the design, build, and deployment of RAG solutions • Drive Agentic development and intelligent automation • Provide guidance on AI architecture and technology strategy • Build and deploy scalable machine learning applications on AWS • Apply ML Ops tooling and workflows More ❯

AI/LLM Engineer/Architect (Contract) - RAG … Implementation| London (mostly remote) - Outside IR35 We're looking for a highly skilled AI/LLM Engineer/Architect to lead the implementation of Retrieval Augmented Generation (RAG) solutions for a major client project in London. This is a hands-on contract role for someone who can build from the ground up - shaping the … steer the organisation's AI stack, define best practices, and ensure the delivery of scalable, cost-effective solutions. What You'll Do • Lead the design, build, and deployment of RAG solutions • Drive Agentic development and intelligent automation • Provide guidance on AI architecture and technology strategy • Build and deploy scalable machine learning applications on AWS • Apply ML Ops tooling and workflows More ❯

AI/LLM Engineer/Architect (Contract) - RAG … Implementation| London (mostly remote) - Outside IR35 We're looking for a highly skilled AI/LLM Engineer/Architect to lead the implementation of Retrieval Augmented Generation (RAG) solutions for a major client project in London. This is a hands-on contract role for someone who can build from the ground up - shaping the … steer the organisation's AI stack, define best practices, and ensure the delivery of scalable, cost-effective solutions. What You'll Do • Lead the design, build, and deployment of RAG solutions • Drive Agentic development and intelligent automation • Provide guidance on AI architecture and technology strategy • Build and deploy scalable machine learning applications on AWS • Apply ML Ops tooling and workflows More ❯

experience building and deploying machine learning models in a production environment. Strong programming skills and deep expertise in Python. Hands-on experience building with agentic or RAG (Retrieval-Augmented Generation) frameworks like LangChain or LlamaIndex. Familiarity with tools for working with Large Language Models via API or in a local context (e.g. HuggingFace transformers More ❯

experience building and deploying machine learning models in a production environment. Strong programming skills and deep expertise in Python. Hands-on experience building with agentic or RAG (Retrieval-Augmented Generation) frameworks like LangChain or LlamaIndex. Familiarity with tools for working with Large Language Models via API or in a local context (e.g. HuggingFace transformers More ❯

understanding their generative AI needs and using platform tools and packages to finetune and iterate on modeling experiments using Large Language Models (LLM) or Retrieval Augmented Generation (RAG). Your experiments should be focused around data and metrics that drive continuous improvement. This includes designing data-driven experiments focused on optimizing model performance by More ❯

and Generative AI R&D. Strong understanding of machine learning, data modelling , and natural language processing (NLP) techniques. Experience with fine-tuning , prompt orchestration , and retrieval methods (RAG, knowledge graphs). Familiarity with frameworks such as LangGraph , Azure AI Foundry Agents , and Semantic Kernel Agents . Good understanding of software engineering best practices , including version control, testing, and More ❯

with productionising and deploying. Strong Python, SQL and programming skills Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment). More ❯

with productionising and deploying. Strong Python, SQL and programming skills Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment). More ❯

with productionising and deploying. Strong Python, SQL and programming skills Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment). More ❯

with productionising and deploying. Strong Python, SQL and programming skills Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment). More ❯

ll Do Define and implement the AI strategy, operating model, and governance structure . Architect and scale AI and ML platforms for enterprise-wide adoption. Lead deployment of LLM, RAG, and Generative AI systems at scale. Partner with business, data, and engineering teams to operationalize AI initiatives. Establish MLOps and LLMOps frameworks for lifecycle automation, compliance, and monitoring. Champion Responsible More ❯

ll Do Define and implement the AI strategy, operating model, and governance structure . Architect and scale AI and ML platforms for enterprise-wide adoption. Lead deployment of LLM, RAG, and Generative AI systems at scale. Partner with business, data, and engineering teams to operationalize AI initiatives. Establish MLOps and LLMOps frameworks for lifecycle automation, compliance, and monitoring. Champion Responsible More ❯

ll Do Define and implement the AI strategy, operating model, and governance structure . Architect and scale AI and ML platforms for enterprise-wide adoption. Lead deployment of LLM, RAG, and Generative AI systems at scale. Partner with business, data, and engineering teams to operationalize AI initiatives. Establish MLOps and LLMOps frameworks for lifecycle automation, compliance, and monitoring. Champion Responsible More ❯

experience in AI/ML solutions on Azure, ideally with Generative AI. Expertise with Azure AI, Azure Machine Learning, and Azure OpenAI Service. Strong Python and PyTorch. Experience of RAG pipeline deployment, prompt engineering, fine-tuning foundation models. Knowledge of Responsible AI principles and AI governance. Strong understanding of cloud-native deployment practices. Excellent communication and stakeholder engagement skills. If More ❯

experience in AI/ML solutions on Azure, ideally with Generative AI. Expertise with Azure AI, Azure Machine Learning, and Azure OpenAI Service. Strong Python and PyTorch. Experience of RAG pipeline deployment, prompt engineering, fine-tuning foundation models. Knowledge of Responsible AI principles and AI governance. Strong understanding of cloud-native deployment practices. Excellent communication and stakeholder engagement skills. If More ❯

experience in AI/ML solutions on Azure, ideally with Generative AI. Expertise with Azure AI, Azure Machine Learning, and Azure OpenAI Service. Strong Python and PyTorch. Experience of RAG pipeline deployment, prompt engineering, fine-tuning foundation models. Knowledge of Responsible AI principles and AI governance. Strong understanding of cloud-native deployment practices. Excellent communication and stakeholder engagement skills. If More ❯

experience in AI/ML solutions on Azure, ideally with Generative AI. Expertise with Azure AI, Azure Machine Learning, and Azure OpenAI Service. Strong Python and PyTorch. Experience of RAG pipeline deployment, prompt engineering, fine-tuning foundation models. Knowledge of Responsible AI principles and AI governance. Strong understanding of cloud-native deployment practices. Excellent communication and stakeholder engagement skills. If More ❯

with Google Cloud Run and Kubernetes (GKE) . Familiarity with GCP data tools like BigQuery and Google Cloud Storage (GCS) . Experience building complex agentic AI applications (beyond basic RAG or LangChain implementations). How We Evaluate Candidates Our interview process is designed to identify practical engineering competence and collaborative skills. Technical Acumen: The technical assessment is rigorous. We evaluate More ❯

Must-Haves: Technical Chops 5+ years software engineering in production environments Strong in Node.js/TypeScript and Python Experience building microservices architectures Hands-on AI/ML integration (LLMs, RAG, agent frameworks) Cloud infrastructure expertise (GCP/AWS/Azure) Real-time systems and async processing experience Leadership 2+ years leading engineering teams (3-10 people) Proven track record hiring More ❯

Must-Haves: Technical Chops 5+ years software engineering in production environments Strong in Node.js/TypeScript and Python Experience building microservices architectures Hands-on AI/ML integration (LLMs, RAG, agent frameworks) Cloud infrastructure expertise (GCP/AWS/Azure) Real-time systems and async processing experience Leadership 2+ years leading engineering teams (3-10 people) Proven track record hiring More ❯

Must-Haves: Technical Chops 5+ years software engineering in production environments Strong in Node.js/TypeScript and Python Experience building microservices architectures Hands-on AI/ML integration (LLMs, RAG, agent frameworks) Cloud infrastructure expertise (GCP/AWS/Azure) Real-time systems and async processing experience Leadership 2+ years leading engineering teams (3-10 people) Proven track record hiring More ❯