201 to 225 of 255 Retrieval-Augmented Generation Jobs in London

ingestion, storage, governance, analytics, model deployment, monitoring, and integration with enterprise applications. Understanding of generative AI solution patterns, such as retrieval‐augmented generation, enterprise search, intelligent assistants, document processing, content generation, and AI‐enabled workflow automation. Awareness of AI governance, responsible … Model Garden, Document AI, Gemini, or other Google Cloud data, analytics, API management, AI, or generative AI services. Experience designing retrieval‐augmented generation architectures using vector search, embeddings, enterprise data sources, access controls, and secure application integration patterns. Experience with MLOps, including model lifecycle ...

tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams. Applies knowledge … multiple modern programming languages including Python, Golang, TypeScript and similar technologies in an AWS/Cloud environment. Experience in the use of GPT, LLM, RAG, Gen AI, Prompt Engineering related technologies Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages ...

platform - including emerging directions such as reinforcement learning (RLHF/RLVR), agent optimization, and other post-training and agentic techniques - enabling the next generation of AI-powered products, agents, automation, and personalization. We’re excited about you because you have... BSc, MSc, or PhD in Computer Science … internal platforms, or self‐serve infrastructure Experience building and deploying AI agents or MCP servers in production Experience with eval systems, LLM observability, tracing, RAG, search, or vector databases Diversity, Equity and Inclusion At the company, we know that a great workplace reflects the world around us and that true ...

platform and infrastructure engineering role - not a data science or ML engineering position. You'll own the runtime, infrastructure, and operational layers that RAG pipelines, LLM orchestration, vector search, and evaluation workflows run on, across AWS and Databricks. The focus is on building scalable, observable, secure, and cost-efficient platform … infrastructure (OpenSearch, Algolia, AWS Bedrock Knowledge Bases) and embedding pipelines Build and maintain CI/CD pipelines for inference services, retrievers, ingestion workflows, and RAG components Implement observability across AI workloads using CloudWatch, MLflow, and OpenTelemetry - covering latency, throughput, cost, and system health Apply secure-by-design principles including ...

qualifications. Tech focus: Python and AWS (or equivalents in Azure or GCP), with hands‐on work across classical ML and modern LLM/RAG systems using services like Amazon SageMaker and Bedrock. What you’ll do Partner with stakeholders across the business to explore high‐impact opportunities. Own the full … lifecycle: problem framing, data discovery, feature engineering, modelling, evaluation, deployment, monitoring, and iteration. Build and productionize LLM features where appropriate (retrieval‐augmented generation, evaluation, safety guardrails, cost/latency optimization) on AWS. Contribute to DS/ML standards: experimentation, model governance, documentation, and reproducibility. ...

financial reporting platform. Engineer Digital Integrated Agents for JTC’s client-facing digital products, enabling non-linear user journeys, content and dynamic UI generation, conversational AI-enabled analytics and reporting, and persona-aware hyper-personalisation services. Deliver the enterprise document extraction platform and agent supporting workflows across service … from prototype through governed production deployment and ongoing operation. Deep hands-on expertise in LLMs and agentic systems: prompt and context engineering, retrieval-augmented generation, tool/MCP orchestration, multi-agent workflows and evaluation frameworks. Experience with the Anthropic stack (Claude, Claude Code, agent ...

consecutive years at one employer, with experience more important than a specific title. Deep expertise in generative AI products, including retrieval‐augmented generation, agentic workflows, and their evaluation. Proven ability to independently drive product strategy and execution across multiple engineering organisations and external dependencies. ...

extract patterns from one‐off work and turn them into reusable assets for others. Applied AI and Agentic Systems Experience building with LLMs, agents, RAG, tool use, workflow orchestration, or automation systems. Ability to reason about multi‐agent, human‐in‐the‐loop, and enterprise integration patterns. Comfort debugging agent behavior ...

leaders to drive AI-enabled transformation across enterprises, leading engagements from discovery to execution and shaping AI strategy. You will translate GenAI, LLMs, RAG into actionable roadmaps, engage C-suite stakeholders, and contribute to revenue growth with strong consulting acumen. The role offers hybrid working across London, Manchester or Glasgow ...

forward-thinking services company at the forefront of AI-native innovation. We partner with enterprise clients to create next-generation, agent-powered workflows engineered to scale in real-world settings. Our engineers embed deeply with customers, moving projects beyond experimentation into operational reality. You are An AI Native … native systems (APIs, microservices, containerization, serverless). Minimum of 1 year of hands-on experience designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production or near-production environments. Experience with modern AI platforms — OpenAI, Claude, Vertex AI, or open-source models — including building or using abstraction ...

operations, and own what you ship. What You'll Do Build and deploy production AI applications using LLMs, including agent workflows, tool use and RAG pipelines over company data Contribute to evaluation frameworks covering accuracy, latency, cost and reliability, with the extra rigour a regulated industry demands Implement retrieval … whether in production, at work or through substantial personal projects, with a genuine understanding of their capabilities, limitations and failure modes Practical familiarity with RAG architectures, vector databases and prompt engineering Exposure to agent frameworks (LangGraph, Claude Agent SDK, OpenAI SDK) or equivalent custom implementations An interest in LLM evaluation ...

tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams. Applies knowledge … multiple modern programming languages including Python, Golang, TypeScript and similar technologies in an AWS/Cloud environment. Experience in the use of GPT, LLM, RAG, Gen AI, Prompt Engineering related technologies Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages ...

reference architectures for investment and front‐to‐back office use cases. Drive integration of AI capabilities with core data platforms and content platforms, leveraging RAG and MCP to unlock proprietary data assets. Governance & Risk: Design and operationalize AI governance, covering model risk management, explainability, bias monitoring, data lineage, and regulatory …/ML architecture in large, complex enterprise environments. Hands‐on command of modern AI stack: LLM APIs and fine‐tuning, vector databases, RAG, embedding pipelines, prompt engineering, and agent orchestration frameworks (LangChain, AutoGen, or equivalents). Practical exposure to agentic AI architecture, multi‐agent coordination, and MCP or similar frameworks. ...

modelling, machine learning, predictive analytics, and decision science delivered into production environments and real business processes. Generative AI (Secondary): LLM‐powered applications such as RAG pipelines and document intelligence, applied where appropriate to support data‐led solutions. Autonomous AI (Emerging): Agent‐based systems and AI workflows, used selectively where they … lifecycle management. Proven ability to translate business problems into data science solutions that deliver measurable outcomes. Beneficial Exposure to Generative AI (e.g. LLMs, RAG) is beneficial but not a substitute for core data science expertise. Awareness of emerging AI paradigms (e.g. agent‐based systems) is a plus, but not required. ...

Experience in cybersecurity, email security, or adjacent enterprise SaaS domains preferred.* Familiarity with AI/ML concepts including prompt engineering, model evaluation, retrieval-augmented generation, and agent orchestration frameworks is valuable but can be developed in-role.* Prior experience in a developer enablement, developer ...

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 ...

automated document classification, geospatial modeling of electric vehicle demand, demand forecasting, predictive maintenance, price optimization, and developing and maintaining production‐grade agentic RAG systems that serve the entire firm. What You’ll Do Data Management Perform data availability/quality assessments Develop comprehensive ETL processes Data Analysis Perform exploratory data … Analysis (Graph Theory), and Regressions Experience in AI/ML concepts: Cross Validation, Ensemble Methods, Over/Under Fitting, Accuracy/Precision/Recall, RAG, Agents Understanding of AI/ML performance measurement best practices including QA/QC framework, drift, bias, and fairness Experience in computer science concepts: Hashing ...

trends within the software industry Built or integrated AI/ML features into products and systems, including recommendation engines, NLP, computer vision, predictive analytics, RAG pipelines, and agents Successfully led modernisation and replatforming efforts to align legacy systems with short and long‐term business needs Led and delivered solutions … 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 How You’ll Be Supported ...

aligned with engineering standards. Comfortable working across technical implementation, team enablement, stakeholder communication, and operational rollout. Curious about areas such as AI agents, MCP, RAG, evals, prompt/workflow design, AI observability, and developer productivity measurement. The Impact You Will Have Help engineering teams adopt AI in a way that … security, and release discipline. Experience with design systems, frontend platform standards, accessibility, and reusable UI patterns. Experience with knowledge retrieval, documentation systems, RAG‐style workflows, or internal engineering knowledge platforms. Experience designing lightweight evaluation approaches for AI‐generated outputs, automation, or agentic workflows. Experience coaching engineers, running workshops ...

PrivateLink for cross-cloud data connectivity. AI Readiness : Practical experience architecting data infrastructure for AI/ML consumption - vector databases, embedding stores, and RAG pipeline integration. Soft Skills: Strong interpersonal skills; ability to translate complex data architecture into clear language for Business Analysts and non-technical stakeholders. Duties Data Modelling … warehouse scheduling strategies to reduce operational data spend. AI Readiness: Architect data stores purpose-built for LLM consumption - including vector databases, embedding pipelines, and RAG-compatible data structures that will serve as the foundation for Bestway's AI product layer. Data Contracts : Partner with Business Analysts to formally define ...

Skills for the Artificial Intelligence Architect: Proven experience architecting solutions across Generative AI, Agentic AI, machine learning and automation Strong understanding of prompt engineering, RAG pipelines, model tuning, MLOps and LLMOps Experience delivering enterprise‐scale RAG solutions using LLMs and vector databases Ability to design AI platforms that integrate with ...

Engineer to design, build, and deploy production-ready Generative AI systems. Role You will own the full lifecycle of GenAI applications, working with LLMs, RAG architectures, and agentic frameworks to deliver scalable, business-focused solutions. Responsibilities Build and deploy GenAI and RAG systems Develop agentic AI workflows Design prompts … clients and technical teams Requirements 1-3 years deploying LLM/GenAI systems in production Strong Python skills Experience with cloud platforms Knowledge of RAG, vector databases, and LLM frameworks Git and CI/CD experience Experience with LangChain and LangGraph AWS experience IT/Technology-related university degree (minimum ...

able to demonstrate and evidence experience of delivering the below: Key criteria: Proven, demonstratable experience in AI-driven and AI-assisted testing, including GenAI, RAG-based systems, intelligent automation, and tools such as GitHub Copilot, Amazon Q, and Cursor AI Proven experience in innovation and PoCs, particularly … test generation and regression optimisation Senior QA/SDET with experience across web, mobile, API, desktop, and cloud testing Expertise in test automation frameworks including Selenium, Playwright, Appium, Rest Assured, and TestNG Capability in designing and delivering scalable automation frameworks and enterprise test strategies Extensive experience ...

booking and customer-service platforms * Automate customer enquiries, lead qualification, booking support and follow-up communications * Build solutions using OpenAI APIs, large language models, RAG, embeddings, vector search and tool calling * Implement permissions, monitoring, escalation processes and data-privacy controls * Integrate third-party systems using APIs, webhooks and data pipelines … WordPress websites, including custom themes, plugins and API integrations * Experience integrating booking engines, ecommerce platforms and payment systems * Practical experience with OpenAI APIs, LLMs, RAG and agentic workflows * Experience integrating CRM platforms, WhatsApp Business, webhooks and third-party APIs * Strong SQL, data-integration and dashboard-development skills * Knowledge of technical ...

booking and customer-service platforms * Automate customer enquiries, lead qualification, booking support and follow-up communications * Build solutions using OpenAI APIs, large language models, RAG, embeddings, vector search and tool calling * Implement permissions, monitoring, escalation processes and data-privacy controls * Integrate third-party systems using APIs, webhooks and data pipelines … WordPress websites, including custom themes, plugins and API integrations * Experience integrating booking engines, ecommerce platforms and payment systems * Practical experience with OpenAI APIs, LLMs, RAG and agentic workflows * Experience integrating CRM platforms, WhatsApp Business, webhooks and third-party APIs * Strong SQL, data-integration and dashboard-development skills * Knowledge of technical ...