9 of 9 Permanent Retrieval-Augmented Generation Jobs in West London

agentic AI. Continuous Learning: Stay updated with the latest trends in the AI engineering field, such as the modern AI stack, synthetic data generation, and Explainable AI. … Skills/Experience: Engineering Foundations: Strong proficiency in Python and robust software engineering principles, with experience operating as part of engineering teams. Generative AI & RAG: Proven experience working with LLMs and designing Retrieval-Augmented Generation (RAG) architectures, including knowledge of semantic search and vector ...

. Experience building pipelines for structured and unstructured data using both vector databases and retrieval-augmented generation (RAG)-like architectures to power enterprise AI solutions. Experience leading technical discovery sessions. Preferred qualifications: Masters degree or PhD in Artificial Intelligence, Computer Science, or a related ...

across a range of AI and cloud projects. Responsibilities will include: Designing and delivering Generative AI and Machine Learning solutions Building applications using LLMs, RAG frameworks and AI orchestration tools Working directly with clients to understand business challenges and define AI-driven solutions Leading architecture and engineering decisions across Azure … experience building AI-powered applications and deploying them into production Software Engineering or Product Engineering background Strong Python development skills Experience working with LLMs, RAG architectures and modern AI frameworks Multi-cloud experience across Azure, AWS and GCP Strong understanding of cloud-native architectures and scalable application design Experience with ...

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 Familiarity with LLMOps tooling such as LangSmith, LangChain, or LangGraph Understanding of model evaluation, validation techniques, and production monitoring Experience working in cross-functional … well 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 ...

architecture and prototyping through to deployment, monitoring and continuous evaluation. Key responsibilities: Design and deliver production GenAI and multi-agent systems Build agentic workflows, RAG solutions, tool use and multi-step orchestration Define evaluation strategies and implement AI observability Design secure AWS deployment architectures Build CI/CD pipelines … skills Hands-on experience with LangGraph, LangChain, LlamaIndex, CrewAI or similar Experience with AWS, particularly Bedrock, Lambda, ECS, EKS or SageMaker Strong understanding of RAG, agentic AI and multi-agent architectures Experience with CI/CD, cloud infrastructure and application deployment Comfortable working directly with clients and senior stakeholders Experience ...

Python in an enterprise, high-bar engineering environment. Demonstrated experience designing, building, and deploying large language model applications, including prompt engineering, evaluation, retrieval-augmented generation, and agent orchestration. Familiarity with modern generative AI components such as large language model APIs, vector stores, embeddings, tool ...

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 ...

.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 ...

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 ...