51 to 75 of 79 Retrieval-Augmented Generation Jobs in London

closely with engineers to translate validated approaches into scalable, customer-facing solutions. Key Responsibilities: Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies, patent search). Define agentic workflows and reasoning strategies for multi-step IP tasks. Develop retrieval strategies, including hybrid search (semantic … Strong experience designing and running experiments, including model evaluation and iteration. Strong coding skills in Python. Experience with generative AI techniques (e.g., prompt engineering, RAG). Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases. Experience designing agentic workflows and reasoning strategies, with hands ...

support critical decision-making processes. The Role Build and deploy agentic AI workflows using tools such as LangGraph and LangChain. Design and optimise RAG pipelines, including vector search, embeddings, and retrieval strategies. Develop LLM-powered applications for document intelligence, classification, extraction, and reasoning. Create evaluation frameworks and observability … building and deploying LLM, generative AI, or machine learning systems in production. Expertise with LangGraph, LangChain, or similar orchestration frameworks. Experience designing and improving RAG architectures and vector database solutions. Knowledge of AI evaluation, observability, and cloud-based software engineering best practices. How to Apply ...

worlds most trusted patent data with sophisticated analytics, AI-powered insights, and purpose-built workflows. Protégé in PatentSight is our clients next-generation agentic AI assistant, purpose-built for strategic patent analysis. Protégé replaces complex filter-based workflows with natural language questions, surfacing structured, decision-ready insights grounded … with experience in a dedicated AI/ML architecture, principal engineer, or distinguished engineer role. Proven track record delivering production LLM-based systems, including RAG pipelines, agentic/tool-use frameworks, and multi-step reasoning workflows. Strong proficiency in Python for AI service development; working knowledge of C# or equivalent ...

days per week Were partnering with an established global technology business looking for a highly experienced Software Engineer to help shape the next generation of a major SaaS platform. This is for someone who still wants to engineer . Not a people-management position disguised as a technical … forefront of that change. Experience with technologies or concepts such as OpenAI, Anthropic Claude, Amazon Bedrock, LLM APIs, coding agents, structured outputs, tool calling, RAG, semantic search, model routing or AI evaluation would be highly relevant. However, we're far more interested in engineering principles, judgement and learning ability than ...

Senior Python AI Developer - Generative & Agentic AI Python FastAPI AWS LLMs RAG Agentic AI DevOps Salary: 60,000 - 75,000 Contract rate: c 475 per day Location: London - Hybrid (3 days per week onsite) Employment: Permanent or Contract 2 positions We're recruiting two experienced Senior Python AI Developers … applications. The role Designing and developing Python backend services and APIs using FastAPI Building Generative AI, Agentic AI and LLM-powered applications Developing RAG architectures, prompt orchestration and AI evaluation tooling Integrating LLMs with enterprise applications and business workflows Working with AWS services including Bedrock, AgentCore ...

Senior Python AI Developer - Generative & Agentic AI Python | FastAPI | AWS | LLMs | RAG | Agentic AI | DevOps Salary: £60,000 - £75,000 Contract rate: c£475 per day Location: London - Hybrid (3 days per week onsite) Employment: Permanent or Contract | 2 positions We're recruiting two experienced Senior Python AI Developers … applications. The role Designing and developing Python backend services and APIs using FastAPI Building Generative AI, Agentic AI and LLM-powered applications Developing RAG architectures, prompt orchestration and AI evaluation tooling Integrating LLMs with enterprise applications and business workflows Working with AWS services including Bedrock, AgentCore ...

.NET, Python, TypeScript, JavaScript, React, Go, Ruby, Scala, R, and SQL Leveraged AI-assistive development tools for tasks like scaffolding, refactoring, debugging, test generation, and documentation Experience building or integrating AI/ML-powered features into products or systems (e.g., recommendation engines, NLP models, computer vision, predictive analytics … platforms, and infrastructure that other teams build on Data Engineering: including platforms like Databricks for data processing and analytics Delivering production agentic systems, including RAG pipelines, vector search, and agentic frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, and n8n DevSecOps & DevOps MLOps Infrastructure as Code Building a truly diverse, equitable ...

session Coaching engineering and product teams on identifying and prioritising AI use cases Helping teams understand and implement technologies such as AI Agents, RAG, LLMs, prompt engineering and automation tools Creating training content, learning modules and enablement programmes Supporting teams through the full lifecycle from idea through to production deployment … Engineering, Solutions Architecture, Platform Engineering or DevOps Strong understanding of production AI solutions, not just AI concepts and demos Experience with AI Agents, RAG, LLMs, APIs, MCP, automation platforms and modern AI tooling The ability to explain technical concepts to both technical and non technical audiences Experience delivering workshops where ...

Developers delivering enterprise-grade Generative and Agentic AI solutions Designing and developing Python and Java services, APIs and AI components Building LLM integrations, RAG architectures and agent-based workflows Developing prompt orchestration, output validation and AI evaluation capabilities Working with AWS services including Bedrock, AgentCore … expect experience across a good mix of: Strong Python, Java and FastAPI development experience Generative AI, Agentic AI and Large Language Models RAG architectures, prompt orchestration and LLM integration AWS cloud engineering, particularly Bedrock and AgentCore CI/CD, DevOps and engineering automation RESTful APIs, microservices and distributed systems Technical ...

SharePoint and Azure AI Search capabilities to AI agents. - Build SharePoint and Microsoft Graph ingestion pipelines for documents, emails and attachments. - Design and implement RAG and agentic AI workflows using Azure OpenAI. - Deliver hybrid search solutions combining semantic and vector retrieval. - Implement secure, permission-aware access controls using Entra … Provide technical leadership and mentorship to a junior engineer. Essential Skills & Experience - MCP server development and AI agent tooling - Azure OpenAI, Azure AI Search, RAG and prompt engineering - SharePoint Online and Microsoft Graph API - Hybrid semantic/vector search - Enterprise API development and document processing - Azure (Functions and/ ...

features and capabilities on an enterprise-grade Generative & Agentic AI application. Experience, and hands on, with Generative and Agentic AI patterns including LLM integration, RAG architectures, prompt-driven workflows, and orchestration of AI services and agents. Develop and optimise Python-based AI components including prompt orchestration, output validation, and evaluation … architects, and design teams to ensure reliable operationalisation of AI services. Support benchmarking, evaluation, and experiment tracking for LLM performance and cost. Contribute to RAG implementations and data access patterns supporting enterprise use cases. Help shape API standards, reusable patterns, and documentation for platform adoption. Troubleshoot and optimise performance across ...

solutions. Lead product discovery activities, business case development and value realisation initiatives. Drive prioritisation and delivery of AI use cases including Copilot, AI Agents, RAG, Knowledge Assistants and Intelligent Automation. Collaborate with Data Engineers, AI Engineers, Architects and business teams throughout the product lifecycle. Manage and refine the product backlog … product management practices. Desirable Skills Experience with Microsoft Copilot, GitHub Copilot and Azure AI Foundry. Knowledge of Databricks Mosaic AI and MLflow. Experience delivering RAG, AI Agent and Knowledge Assistant solutions. Background in Management Consulting or Digital Transformation. Experience working across Data Engineering, AI Engineering and Analytics teams. Exposure ...

architects, and SRE teams to ensure reliable operationalisation of GenAI services. Support benchmarking, evaluation, and experiment tracking for LLM performance and cost. Contribute to RAG implementations and data access patterns supporting enterprise use cases. Help shape API standards, reusable patterns, and documentation for platform adoption. Troubleshoot and optimise performance across … experience with GitOps workflows. Prompt redteaming & evaluation tools (like Promptfoo & Arize). Experience with SQL (MySQL, PostgreSQL) and NoSQL (MongoDB, Cassandra) databases Exposure to RAG patterns and vector search technologies. Behavioural Competencies Proactive self-starter who identifies gaps and drives solutions without waiting for tickets. Comfortable working in ambiguous emerging ...

Power Platform APIs, connectors, identity and permissions Enterprise data integration and governance You should also understand practical Generative AI concepts, including grounding, retrieval-augmented generation, prompt design, hallucination management and secure access to organisational data. Strong stakeholder-management and consulting skills are essential. ...

building production-grade LLM systems used to solve complex knowledge and workflow challenges. This is a hands-on opportunity to work on agentic AI, RAG and evaluation frameworks in a highly technical, fast-moving environment. The Company They are building an AI platform that helps organisations automate complex workflows … they combine startup agility with strong commercial foundations. The Role Build multi-step AI agent workflows using LangGraph, LangChain or similar frameworks Develop production RAG pipelines, embeddings and retrieval systems Design AI evaluation frameworks and testing infrastructure Optimise model performance, reliability, latency and cost Build backend services ...

Senior Software Engineer to join a growing AI team and take ownership of the application and integration layer behind a new generation of AI-powered products. This is a genuinely full-stack engineering role, combining production-grade backend development, API design, AI integrations and frontend engineering. … securely and reliably. Experience working closely with designers to deliver production-quality frontend applications. A good understanding of accessibility and frontend performance. Experience with RAG, AI agents, tool use or other generative AI application patterns would be advantageous, although deep ML expertise isn't required. This is an opportunity ...

GenAI and automation to solve business and operational problems. Design, prototype and deploy AI-enabled workflows and agentic solutions using technologies such as LLMs, RAG, LangGraph/LangChain and APIs. Analyse complex workflows, data and processes and translate problems into clear technical solutions. Work closely with Product and Engineering throughout … delivery, AI or a similarly technical environment. Hands-on experience designing, building and deploying AI agents or GenAI solutions. Practical knowledge of agentic AI, RAG, LLMs, APIs and automation, ideally including LangGraph or LangChain. Strong understanding of software development, combined with excellent analytical and problem-solving skills. Comfortable working directly ...

enterprise AI platform across Azure and AWS. Design capabilities for ML training, model hosting, MLOps and Generative AI. Define architecture patterns for LLMs, RAG, vector search and agent-based frameworks. Evaluate AI technologies and select appropriate tooling based on technical, security and cost requirements. Produce architecture blueprints, technical standards, reference … security. Deep understanding of MLOps , model training pipelines, orchestration, feature stores, model hosting and observability. Strong Generative AI architecture experience, including LLM hosting, RAG, vector databases, prompt orchestration and guardrails. Knowledge of AI platform tooling such as Azure ML, Amazon SageMaker, MLflow, Kubeflow and Databricks . Ability to evaluate technologies ...

legal, data protection, risk and responsible AI stakeholders. * Design secure architectures for Microsoft 365 Copilot, Copilot Studio, AI agents, custom AI applications, retrieval-augmented generation, Azure AI services, third-party models and Model Context Protocol integrations. * Own the technical security control catalogue ...

release management and vendor support. Applied AI & Agentic Workflows: Experience building agentic workflows that combine models, tools and business data, including orchestration, retrieval-augmented generation and evaluation. Familiarity with Google ADK or similar frameworks is desirable. API & Data Integration: Strong knowledge of REST APIs ...

that includes conversational, Agentic AI's. This role focuses on building advanced conversational AI systems, implementation AI Agents across different use cases, implementing sophisticated RAG architectures, and deploying production-grade voice AI applications. This is a newly created role in a rapidly growing business. A brilliant opportunity! The following skills …/experience is essential: Hands-on experience with advanced RAG systems Strong experience with LLM technologies Agentic AI experience Software Engineering background Good communication skills Salary: Up to £95,000 + bonus + package Location: London (good work from home options available) If you are interested in this Senior ...

prototype to production, solving complex business challenges through LLMs, autonomous agents and intelligent automation. Key Responsibilities Build and deploy single and multi-agent systems, RAG pipelines and AI-powered workflows. Work with leading AI platforms and frameworks, including OpenAI, Anthropic, Google, Microsoft and LangGraph. Integrate AI solutions with enterprise APIs … years of software engineering experience in Python, TypeScript, Java or similar languages. Hands-on experience building LLM-powered applications and AI agents. Understanding of RAG, tool-calling, agent orchestration and multi-agent workflows. Experience with APIs, databases, cloud platforms and enterprise integrations. Strong debugging, testing and problem-solving skills. Comfortable ...

real client data during Assess engagements - the prototype is the discovery tool, built while the value case is made Delivering client POCs and MVPs: RAG pipelines, agent architectures, LLM integrations and protocol-driven tooling (MCP, tool orchestration) Iterating in short loops: demoing every few days, taking feedback, changing course without … production mindset) Hands-on experience with LLMs - this can come from personal projects, not just professional work (API integrations, prompt engineering, agent workflows, RAG systems) Proficiency in 2+ modern programming languages Awareness of evolving AI tooling (MCP, A2A, or similar) Some consultancy or client-facing experience, or a strong interest ...

commercial models such as licensing, entitlement, packaging or pricing is an advantage Familiarity with how AI applications consume content, for example retrieval-augmented generation, agents, or text and data mining, is a plus Superb verbal, written, and interpersonal communication skills and a demonstrated ability ...

doing Building AI applications, copilots, agents and automated workflows Developing solutions using Azure OpenAI, Azure AI services and Copilot Studio Building RAG and enterprise search solutions using internal business data Connecting AI solutions into platforms such as Microsoft 365, SharePoint, Dataverse and other business systems Working with APIs, connectors … Microsoft ecosystem. Ideally, your background will include several of the following: Azure OpenAI Azure AI Foundry Copilot Studio Microsoft 365 Copilot Azure AI Search RAG/knowledge-grounded AI applications AI agents and agentic workflows Microsoft Fabric Power Platform Azure Functions/Logic Apps APIs and system integrations Python, C# ...