176 to 200 of 218 Retrieval-Augmented Generation Jobs in England

agents on GCP using Google’s ADK Integrate AI systems with policy, claims and CRM platforms via REST/JSON APIs Develop scalable RAG pipelines including ingestion, text processing and vector search Implement evaluation, monitoring, A/B testing and cost/latency dashboards Shape architectural patterns, engineering standards … expertise in GCP (Vertex AI, BigQuery, Cloud Run/Functions, ADK, Model Garden) Strong Python and API development experience Hands‐on with LLMs, embeddings, RAG, vector databases Proven track record building production‐ready AI systems with observability and testing Solid DevOps capability: CI/CD, Docker, Kubernetes Work Environment & Location ...

capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge. We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People … Langchain, AutoML, OCR, STT, feature stores, vector DB Implementation of AI/ML architectural patterns and best practices e.g. data drift detection, experimentation tracking, RAG, deployment models Building and using cloud-based solutions (networking, security, storage, monitoring, scaling, DR/HA) on one or more cloud platforms SW Engineering ...

/B experiments and performance dashboards. • Integrate AI agent functionality with applications through MCP servers and reliable tool configurations. • Develop secure and scalable RAG pipelines, including ingestion, text processing, metadata handling and vector search in GCP. • Embed security, compliance, GDPR controls and best‐practice engineering with clear documentation and stakeholder … Strong Python skills for backend services, SDKs, API development, authentication and testing. • Hands‐on experience working with LLMs, embeddings, prompt engineering, tool calling and RAG design. • Practical knowledge of GCP services including Vertex AI, Model Garden, BigQuery, Cloud Run and Google’s ADK. • Experience with document and data processing using ...

/B experiments and performance dashboards. • Integrate AI agent functionality with applications through MCP servers and reliable tool configurations. • Develop secure and scalable RAG pipelines, including ingestion, text processing, metadata handling and vector search in GCP. • Embed security, compliance, GDPR controls and best‐practice engineering with clear documentation and stakeholder … Strong Python skills for backend services, SDKs, API development, authentication and testing. • Hands‐on experience working with LLMs, embeddings, prompt engineering, tool calling and RAG design. • Practical knowledge of GCP services including Vertex AI, Model Garden, BigQuery, Cloud Run and Google’s ADK. • Experience with document and data processing using ...

platform. Key responsibilities include: Designing, training and deploying AI and ML models on complex, large-scale data. Building GenAI solutions using techniques such as RAG and frameworks like LangChain and related tooling. Working full-stack across data ingestion, feature engineering, modelling and serving. Combining modern GenAI approaches with classical machine … Experience Strong commercial experience as an AI, ML or Machine Learning Engineer working on end-to-end solutions. Hands-on experience with GenAI, including RAG and tools such as LangChain or similar frameworks. Proficiency in Python and experience working with a modern cloud environment, ideally GCP. Confidence working across ...

powered tools, systems and agents to streamline sourcing, research, diligence, and portfolio monitoring Design and deploy end-to-end LLM applications including research copilots, RAG systems, workflow automation, data enrichment, and deal intelligence tooling Ingest, clean, and analyse external datasets through scripts, pipelines, and lightweight ML components Integrate third-party … applied AI engineering, ML engineering, or forward deployed roles Strong Python Experience building and deploying LLM applications (OpenAI, Anthropic, Gemini, etc.) Deep familiarity with RAG methodologies, embeddings, and vector databases (Pinecone, Weaviate, pgvector) Robust API integration experience, including working with third-party datasets, web APIs, or scrapers A product mindset ...

join a fast-growing London team working on cutting-edge AI solutions. You’ll help build and scale large language model (LLM) pipelines , RAG systems , and production-ready AI platforms. What You’ll Do Develop and maintain Python-based LLM/RAG pipelines. Design and deploy scalable AI systems … products. What We’re Looking For Strong Python experience and familiarity with AI/ML frameworks. Hands-on experience with LLM pipelines, embeddings, and RAG systems. Experience with cloud platforms (AWS, GCP) and containerization is a plus. Degree in Computer Science or equivalent practical experience. Problem-solving mindset, adaptable ...

functionally with Product, Engineering and leadership to turn customer problems into production AI systems Influence the adoption of state-of-the-art approaches across RAG pipelines, evaluation frameworks, agent tooling, and prompt engineering Build AI products that deliver real commercial value, balancing experimentation with scalable delivery What they’re looking … Deep experience across Generative AI, LLMs and classical machine learning Strong hands-on engineering background (Python, PyTorch, ML frameworks) Experience with agentic AI systems, RAG pipelines, and modern AI tooling A leader who can mentor teams, shape strategy, and drive delivery in fast-moving environments The role ...

Applied AI Software Engineer - LangChain, LangGraph, RAG, Knowledge Graphs A high-growth, technology-led scale-up (backed by a global leading organisation) is expanding its engineering capability following a highly successful 2025. As part of significant continued investment, they are hiring a Software Engineer to lead the design and development … next-generation AI products and services across Finance, supporting both internal operations and external platforms. This is an opportunity to work in a modern, cloud-native engineering environment, building intelligent agentic AI systems that can reason, plan and act autonomously. You will take ownership of solutions ...

needs to work. 50+ models in production. Real clients. Real scale. The role You'll own LLM applications end to end. Architecture, prompt engineering, RAG pipelines, eval tooling, guardrails, all of it. No handoffs, no red tape. You build it, you own it. Stack: LangChain/LangGraph, AWS Bedrock, Pinecone … DeepEval/Langfuse, Docker, Python. Multimodal capability essential. What we're looking for 2+ years building and deploying production LLM systems Hands-on with RAG, vector databases and retrieval optimisation Eval tooling experience: DeepEval, Langfuse, Ragas or equivalent Strong Python and LLM orchestration frameworks Multimodal LLM experience (text ...

influence technical strategy, architecture, and best-practice from day one. THE ROLE: Build and operate production-ready AI agents on GCP Design robust RAG pipelines covering ingestion, text processing, vector search and secure data handling. Implement evaluation frameworks, monitoring, A/B testing and performance dashboards for latency, cost … Engineering or Software Engineering with applied AI delivery. Deep hands-on expertise with GCP services Strong Python skills Practical experience with LLMs, embeddings, RAG architectures and vector databases. A track record of building production-grade AI systems, including observability, evaluation and automated testing. DevOps capability across CI/CD, Docker ...

influence technical strategy, architecture, and best-practice from day one. THE ROLE: Build and operate production-ready AI agents on GCP Design robust RAG pipelines covering ingestion, text processing, vector search and secure data handling. Implement evaluation frameworks, monitoring, A/B testing and performance dashboards for latency, cost … Engineering or Software Engineering with applied AI delivery. Deep hands-on expertise with GCP services Strong Python skills Practical experience with LLMs, embeddings, RAG architectures and vector databases. A track record of building production-grade AI systems, including observability, evaluation and automated testing. DevOps capability across CI/CD, Docker ...

powered tools, systems and agents to streamline sourcing, research, diligence, and portfolio monitoring Design and deploy end-to-end LLM applications including research copilots, RAG systems, workflow automation, data enrichment, and deal intelligence tooling Ingest, clean, and analyse external datasets through scripts, pipelines, and lightweight ML components Integrate third-party … applied AI engineering, ML engineering, or forward deployed roles Strong Python Experience building and deploying LLM applications (OpenAI, Anthropic, Gemini, etc.) Deep familiarity with RAG methodologies, embeddings, and vector databases (Pinecone, Weaviate, pgvector) Robust API integration experience, including working with third-party datasets, web APIs, or scrapers A product mindset ...

deployments, including LLMs, agentic models, AI orchestration frameworks, and ML-powered personalisation. Strong interest in emerging AI paradigms (e.g., autonomous agents, retrieval-augmented generation, model fine‐tuning), with the ability to evaluate their feasibility and strategic impact. Experience developing platform or product strategy within ...

want to shape how LLMs are deployed at scale in a real business? Have you built RAG or agentic systems that moved beyond experimentation? Are you motivated by measurable customer and commercial impact, not demos? A private-equity-backed consumer services business is scaling its Data Science & AI capability … year transformation. Following an award-winning data programme, the company now has an established AI function and is investing further in LLM-powered assistants, RAG pipelines, voice/chat intelligence and early agentic workflows across both customer-facing and internal products. This Senior AI Engineer role is a hands ...

services, and developer tooling that make AI easy to adopt across teams Designing and operating agent-based and multi-model workflows Building and scaling RAG pipelines, retrieval services, and vector search infrastructure Improving the reliability , latency, observability, and cost-efficiency of AI workloads Putting the right security, governance … applications, AI/ML platforms, or production AI systems Familiarity with agent frameworks, orchestration patterns, or multi-model workflows Experience with RAG, embeddings, vector databases, or retrieval systems Strong CI/CD and infrastructure-as-code skills An understanding of what it takes to run AI in production ...

private and public sector clients across 70 countries. The companys technology independence, global talent, and extensive partner network combine to deliver powerful next-generation IT services and solutions. DXC Technology is recognized among the best corporate citizens globally. Were looking for a talented and forward-thinkingAI Engineerto join … Understanding and hands-on experience with Transformer models and LLMs (e.g., GPT, LLaMA, Mistral, Claude). Skills in fine-tuning, prompt engineering, and building RAG pipelines. Familiarity with Agent Frameworks (LangChain, LlamaIndex, CrewAI, AutoGen). Knowledge of reinforcement learning methods or tools (Q-learning, policy gradients, RLlib). Why Join ...

enterprise-grade AI capabilities. What Youll Be Doing Designing and building Copilot solutions, intelligent agents, and LLM workflows Developing scalable AI components including RAG pipelines, embeddings, and vector search Integrating AI solutions into enterprise systems, APIs, and cloud platforms Conducting rapid prototyping to validate use cases, UX, and model performance … Essential Skills for the AI product developer Proven experience building solutions using LLMs, AI APIs, and Copilot Studio or similar tools Strong understanding of RAG architectures, vector databases, and embeddings Experience with Azure AI and cloud-native development Solid knowledge of secure engineering practices including authentication, data protection, and auditability ...

close partnership with some of the world’s leading AI labs. Responsibilities: Lead the design and build production-grade systems using LLMs Working across RAG pipelines, vector databases, and agentic workflows Take AI from concept to real-world impact across industries like financial services, energy, and healthcare Liaise with stakeholders … Proven experience building applications with LLM APIs, with a strong understanding of their real-world capabilities, limitations, and failure modes Hands-on experience implementing RAG architectures, vector databases, knowledge graphs, and effective prompt/context engineering Experience designing and developing multi-step LLM workflows and agent-based systems Strong programming ...

Responsibilities • Build AI PoCs and MVPs in fast innovation cycles (2–6 weeks) • Develop GenAI solutions using LLMs, SLMs and vision models • Implement RAG pipelines and agentic workflows • Build lightweight APIs using Flask or Django • Deploy solutions using serverless and cloud-native services • Collaborate in client workshops, demos and innovation … Salary: £70k–£85k base (flexible for strong profiles) • Working model: Hybrid, 3 days per week in London office • Tech stack: Python/JavaScript, GenAI (RAG, LangChain, LlamaIndex), agentic frameworks, Azure/AWS • Visa: No sponsorship available Interested? Please apply below. ...

take ownership of core parts of the agentic AI stack end-to-end, including: Designing and deploying multi-agent systems Building and scaling RAG-based architectures Developing evaluation frameworks focused on performance, reliability, and safety Delivering AI-powered features used by enterprise clients in production You’ll also be hands … monitoring Experience with tools/frameworks like LangGraph, ReAct, CoT — or ability to build systems from first principles Familiarity with PyTorch/TensorFlow, RAG pipelines, vector DBs, and modern infra Background in startups (builders) or consultancies (client-facing delivery) Self-directed, adaptable, and comfortable operating in ambiguity #AgenticAI #AIJobs #SoftwareEngineeringjobs ...

implementation and data analysis. Job Requirements: Advanced proficiency in Machine Learning and Data Science. Intermediate proficiency in Amazon Sagemaker. Experience with Retrieval-Augmented Generation, Software Development Life Cycle, and Model Context Protocol. Strong problem-solving skills and the ability to contribute to key decisions. ...

internal operations and develop new intelligent products. Their AI capability is expanding quickly, creating strong opportunities for growth. The Role * Build AI solutions across RAG, agentic workflows, and LLM applications.* Develop automation tools, chatbots, and content generation systems.* Work with AWS, LangChain, and vector databases.* Contribute to both … internal and future client-facing products. Your Skills and Experience * Strong commercial experience with RAG, agents, and LLM tooling.* Confident with Python, AWS, and LangChain or similar frameworks.* Hands on with vector databases and retrieval pipelines.* Comfortable identifying problems and delivering end-to-end solutions ...

repeatable outcomes. Experience automating human-centric processes such as approvals, performance reviews, document generation, or analytics workflows. Familiarity with APIs, integration frameworks, RAG-style workflows, vector search, or orchestration tools (nice to have). How to Apply If you're an AI Engineer who wants to make ...

attention to detail. Ability to work effectively within Agile squads and cross-functional environments. Desirable: Exposure to AI testing methods (e.g., validating LLM outputs, RAG consistency, AI behaviour evaluation). Experience using AI-powered QA tools or test-generation frameworks. Knowledge of cloud environments (AWS/Azure ...