76 to 100 of 236 Retrieval-Augmented Generation Jobs in London

technologies Experience architecting scalable AI and ML solutions across serverless, containerised or GPU enabled environments Experience with LLMs, prompt engineering, embeddings, semantic search and RAG patterns Exposure to vector databases and agent frameworks such as LangChain, LangGraph or similar technologies Understanding of MLOps, LLMOps and model lifecycle management principles Experience ...

skills, ideally including FastAPI. Strong AWS experience, including services such as Bedrock, Lambda, ECS/EKS, API Gateway and S3. Experience with LangChain, LangGraph, RAG, vector databases and multi-agent systems. Experience building APIs, platforms, tools and AI-enabled products. Familiarity with evaluation and observability tools such as Arize, Promptfoo ...

preferred) and modern MLOps practices. Commitment to people development: mentoring, performance conversations, and building high‐performing teams. Bonus: experience with NLP on financial contracts, RAG or LLM‐based applications on structured data, large‐scale loan data pipelines, or containerization tooling (Docker, Kubernetes, Terraform). Competitive salary and performance‐based bonus. ...

individual demos.Understanding of Azure security and identity controls as they apply to AI workloads: managed identities, private endpoints, and data residency.Develop and deploy RAG-based knowledge systems using Azure AI Search, Azure OpenAI Service, and relevant orchestration frameworks (LangChain, Semantic Kernel, or Prompt Flow).Design and implement AI agent architectures ...

services, model integration, model monitoring, evaluations, and deployments. Integrate and optimise LLMs for specific use cases in business planning, including prompt engineering and RAG implementation. Build cutting‐edge conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language. Implement evaluation frameworks to measure and improve GenAI ...

production LLM workflows, including prompt/skill design, evaluation, cost control, provider routing, agentic/human‐in‐the‐loop orchestration, embeddings, vector search and RAG Implementation of foundational ML algorithms, classic NLP techniques and LLMs Strong SQL for analytical and production use, ideally PostgreSQL, including complex joins, CTEs and aggregation ...

backend API services, model integration, model monitoring, evaluations and deployments Integrate and optimise LLMs for specific use cases in business planning, including prompt engineering, RAG implementation Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language Implement evaluation frameworks to measure and improve GenAI feature ...

based microservices for scalable, high-throughput architectures* Experience in cybersecurity, SIEM, SOAR, or adjacent security domains* Hands-on experience with LLM integration, prompt engineering, RAG pipelines, or agentic AI frameworks#LI-GO1#LI-HYBRID **Benefits of Working at CrowdStrike:*** Market leader in compensation and equity awards* Comprehensive physical and mental wellness programs ...

understand what makes agents perform well in production and how to systematically improve quality through observability and evaluation. Experience with voice AI platforms, RAG systems, and LLM orchestration frameworks is highly desirable. You bring exceptional communication skills, customer empathy, and the drive to build AI solutions that transform enterprise operations … integration Proficiency in Python (production-grade, async programming, type hints) and JavaScript/TypeScript (full-stack development) RAG implementation experience built retrieval-augmented generation systems with vector databases MLOps & deployment hands-on with Docker, Kubernetes, CI/CD pipelines, and infrastructure-as-code Cloud ...

Lead Strategic Discovery: Identify high‐impact AI opportunities by running hands‐on workshops and aligning stakeholders. Architect AI‐Native Solutions: Design systems using LLMs, RAG pipelines, retrieval logic, and workflow orchestration. Accelerate Delivery with Engineers: Collaborate closely with FDSEs to build, test, and iterate functional solutions quickly. Codify … over at least 3+ years. Technical Mastery: Strong grasp of LLM‐based systems and GenAI pipelines including prompt engineering, retrieval‐augmented generation (RAG), orchestration, and data modeling. Experience designing full‐stack intelligent workflows. Cloud & Infrastructure Fluency: Deep hands‐on experience with AWS, Azure ...

ongoing optimisation of token usage and compute cost across AI workloads. Some Other Highly Valued Skills May Include Retrieval Augmented Generation (RAG) and vector database implementation, with practical experience using technologies such as OpenSearch, FAISS or similar to support scalable, production‐ready retrieval ...

ideally TypeScript/React for front end UI) and Java, and comfortable building production systems directly. Deep understanding of LLMs, retrieval‐augmented generation (including hybrid retrieval across semantic, graph and keyword search, with reranking and embedding‐model selection), knowledge bases, knowledge graphs ...

usable, performant ways for brokers and analysts. AI‐Enabled Development: Build AI‐enabled product features using patterns such as retrieval‐augmented generation, tool and API integration, evaluation and human‐in‐the‐loop design. AI‐Assisted Engineering: Use AI‐assisted engineering tools such as Claude ...

5+ years experience within software development and AI related rolesStrong experience building GenAI/Applied AI solutionsHands-on with LLMs, AI Agents, Agentic Workflows & RAG Proficiency in Python (TypeScript beneficial)Full-stack development with React, Next.js or SvelteAPI and backend development, including scalable microservicesExperience with SQL, NoSQL and Vector DatabasesCloud ...

Knowledge of Airflow, Kafka, Flink, dbt, Kubernetes is highly beneficial. Good understanding of AI platforms, experience building infrastructure for LLM orchestration (e.g., vector databases, RAG pipelines, GPU scaling) is a significant plus. #J-18808-Ljbffr ...

Python and JavaScript Hands-on experience with backend frameworks and modern frontend frameworks Deep knowledge of Generative AI and agent-based AI frameworks including RAG and orchestration patterns Strong experience working with vector databases and AI-specific data stores Solid understanding of AI and ML models, LLMs and generative ...

GitHub, Kubernetes, containerisation or equivalent enterprise DevOps platforms. Experience supporting AI, machine learning, data science, analytics or automation teams. Experience with LLM application architecture, RAG, vector stores, orchestration frameworks, model APIs or context management. Experience integrating third‐party or public data APIs into enterprise environments. Experience defining platform operating models ...

scientific, engineering, or R&D workflows encompassing experimentation, simulation, optimisation, physics-informed modelling, and autonomous scientific workflows. Strong experience with generative AI (LLMs, RAG, multimodal systems) and their deployment in production. Experience designing or deploying Agentic AI systems including autonomous agents, tool use, multi-agent orchestration, reasoning workflows, and agent ...

APIs, workflows, business systems and human‐in‐the‐loop processes Strong understanding of LLM capabilities and limitations, including prompt design, retrieval‐augmented generation, hallucination management, tool use, evaluation and monitoring Experience with AI governance and responsible AI, including agent governance, access controls, data protection ...

backend services. Full-stack development experience is a distinct advantage.* Extensive hands-on experience with **Generative AI concepts, Large Language Models (LLMs), transformer architectures, RAG, and advanced agentic frameworks** (e.g., LangChain, LangGraph, Google ADK. Optionally AutoGen, CrewAI, LlamaIndex, Semantic Kernel).* Deep comfort and practical experience with **containers and orchestration ...

backend services. Full‐stack development experience is a distinct advantage. Extensive hands‐on experience with Generative AI concepts, Large Language Models (LLMs), transformer architectures, RAG, and advanced agentic frameworks (e.g., LangChain, LangGraph, Google ADK. Optionally AutoGen, CrewAI, LlamaIndex, Semantic Kernel). Deep comfort and practical experience with containers and orchestration ...

Familiarity with AI/ML tools such as LangChain, Haystack, Hugging Face, Weaviate, or similar ecosystems. Hands-on experience with Retrieval Augmented Generation applications, AI agents & systems built around them. Experience using GenAI frameworks such as LlamaIndex, Crew AI, AutoGen, or similar agentic/… rapidly build & deploy AI solutions that solve high-priority business problems. Evaluate & integrate existing AI tools, frameworks, & APIs (e.g., LLMs, vector DBs, retrieval-augmented generation, AI agents) into robust applications. Champion automation in workflows—from data management ingestion & preprocessing to evaluation, to model integration ...

multi‐modal large language models across text, image, audio, and video Design and implement agentic workflows using prompt engineering, Retrieval‐Augmented Generation (RAG), APIs, and enterprise data integrations Fine‐tune, optimize, and deploy large language and multi‐modal models with a focus on scalability ...

agent system behind our AI doctor: reasoning, planning, tool use, clinical citation, and safe fallback behavior Retrieval & knowledge — vector infrastructure, embedding pipelines, RAG architecture over clinical literature and user health data. You know the difference between retrieval that works and retrieval that a clinician ...

widely across the organisation. Qualifications Strong software engineering background with modern AI technologies. Hands‐on experience building LLM‐powered systems in production, including agents, RAG pipelines, MCPs, tool‐use and multi‐step workflows. Familiarity with frameworks such as LangGraph, Pydantic AI or similar. Strong Python engineering skills and ability ...