451 to 475 of 884 Retrieval-Augmented Generation Jobs in England

ground truth dataset quality, and guide product development roadmapWhat you’ll need to succeedExperience with building Generative AI Solutions (Prompt engineering, designing and building RAG frameworks, validation pipelines, observability and monitoring solutions)Experience in a traditional data science role, preferably in python, working in an agile production orientated environment, handling ...

service patterns, and database modelling with PostgreSQL. Experience building or working closely with LLM‐powered or agentic systems using Python. Prompt engineering, tool use, RAG, agent orchestration frameworks, or similar. Proficiency with AI‐assisted development tools (e.g. GitHub Copilot, Cursor, Claude Code). 5+ years experience delivering software products ...

dataset quality, and guide product development roadmap **What you’ll need to succeed** * Experience with building Generative AI Solutions (Prompt engineering, designing and building RAG frameworks, validation pipelines, observability and monitoring solutions)* Experience in a traditional data science role, preferably in python, working in an agile production orientated environment, handling ...

code You have experience working with large-scale, unstructured text data and LLMs — including prompt design, evaluation (e.g., golden sets, LLM-as-judge), and RAG patterns You have demonstrated ability to mentor junior data scientists, balance speed, risk, and analytical rigor You have experience with advanced visualization techniques/best ...

exactly once. Bonus points Previously founded a company. Startup experience. Design tooling literacy (Figma), or a design background. Experience with LLM‐backed product features: RAG, embeddings, evaluation. Go, or a willingness to learn it. It's what most of our backend is written in. Data or analytics engineering experience (Python ...

quality codeYou have experience working with large-scale, unstructured text data and LLMs — including prompt design, evaluation (e.g., golden sets, LLM-as-judge), and RAG patternsYou have demonstrated ability to mentor junior data scientists, balance speed, risk, and analytical rigorYou have experience with advanced visualization techniques/best practices ...

work forward independently. What makes you stand out? Experience building AI/LLM-enabled products in production or controlled enterprise environments (e.g. agentic workflows, RAG, prompt engineering, evaluation and governance patterns) Experience with React/Next.js and modern web tooling. Familiarity with document/NoSQL stores (e.g. MongoDB) and data ...

work forward independently. What makes you stand out? Experience building AI/LLM-enabled products in production or controlled enterprise environments (e.g. agentic workflows, RAG, prompt engineering, evaluation and governance patterns) Experience with React/Next.js and modern web tooling. Familiarity with document/NoSQL stores (e.g. MongoDB) and data ...

productive teams DesirableExperience leading teams in fast-growing startups or enterprise software companies Knowledge of financial planning, analytics, or business intelligence domains Experience with RAG systems, vector databases, and semantic search Familiarity with model fine-tuning, evaluation, and continuous improvement workflows Background in distributed systems, microservices, or cloud-native architectures ...

know what it means to balance craft, ownership, and speed Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering Prior experience with React, TypeScript, and/or Go Previous roles where you interfaced with customers or led technical projects with external ...

know what it means to balance craft, ownership, and speed Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering Prior experience with React, TypeScript, and/or Go Previous roles where you interfaced with customers or led technical projects with external ...

know what it means to balance craft, ownership, and speed Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering Prior experience with React, TypeScript, and/or Go Previous roles where you interfaced with customers or led technical projects with external ...

know what it means to balance craft, ownership, and speed Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering Prior experience with React, TypeScript, and/or Go Previous roles where you interfaced with customers or led technical projects with external ...

know what it means to balance craft, ownership, and speed Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering Prior experience with React, TypeScript, and/or Go Previous roles where you interfaced with customers or led technical projects with external ...

know what it means to balance craft, ownership, and speed Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering Prior experience with React, TypeScript, and/or Go Previous roles where you interfaced with customers or led technical projects with external ...

components and tools for routing and making optimal use of various models.LLM & Agentic Infrastructure: Implement advanced context management, tool-use (MCP), skill tooling, and RAG to enhance research workflows and help scale our agentic infrastructure.Evaluation Frameworks: Build rigorous testing for probabilistic systems to ensure model reliability and safety. Build ...

covers the full AI/ML engineering lifecycle, from discovery to deployment and monitoring. Responsibilities include Designing and implementing agentic systems using techniques spanning RAG, grounding, prompt engineering, and orchestration on a GCP-first stack. Building and maintaining production ML pipelines and services for non-GenAI use cases (e.g. recommender … Terraform), experiment tracking, model registry, and monitoring. Proven experience deploying and operating ML systems in production (batch and real-time). Familiarity with RAG architectures, prompt engineering, guardrails and evaluation techniques. Previous experience developing agentic capabilities, such as agent skills, MCP servers, tool usage. Strong grasp of security, privacy ...

prototypes, products and production ready solutions·Designing and implementing end to end AI solutions that integrate with enterprise systems·Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning·Developing AI agents and agentic workflows using modern frameworks·Working with vector databases, APIs and modern data platforms·Supporting … creating a collaborative, high performing environmentExperience Required:·Strong Python and SQL experience·Applied AI engineering, ML engineering or software engineering background·Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning·Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks·Experience with vector databases such as Pinecone, Chroma ...

reduction in repeat manual work.Secure AI Application and Cloud-AI GuardrailsDefine secure design patterns for AI-enabled applications, including LLM-based features, retrieval-augmented generation, AI agents, AI APIs, copilots, and automation workflows.Establish cloud security requirements for AI workloads, including identity, secrets, data storage … NIST AI Risk Management Framework, NIST Generative AI Profile, OWASP Top 10 for LLM Applications, or Cloud Security Alliance AI security guidance.Experience with RAG architecture, AI agents, vector databases, AI APIs, prompt engineering, or AI application threat modelling.Experience building security knowledge assistants, prompt libraries, AI-assisted review workflows, or security ...

Lead from inside the work, not above it, including engineering capabilities and writing code as appropriate. Architect and implement end-to-end retrieval-augmented generation pipelines, including parsing, ingestion, chunking strategy, embeddings, vector storage, retrieval, and prompt management. Build agents and agentic ...

ensuring alignment between business needs, architecture and delivery execution.BUSINESS & AI PROFICIENCYDeep understanding of Generative AI technologies, including large language models, prompt engineering, retrieval-augmented generation, orchestration frameworks and evaluation techniques. Strong experience in solution architecture and design for AI systems, including integration with enterprise ...

technology teams to optimise semantic models for AI readiness.Apply data science, machine learning, NLP, and advanced analytics techniques to enhance insight generation and anomaly detection.Contribute to the organisation's long-term Data & AI strategy, influencing senior stakeholders and executive leadership.Establish best practices, standards, and governance frameworks for responsible … evolving environments where you can shape direction and define solutions.Desirable ExperienceMicrosoft Copilot, Azure OpenAI, or similar AI platforms.Retrieval-Augmented Generation (RAG) and semantic grounding techniques.Executive-level analytics solutions and trusted AI implementations.Highly regulated or data-governed environments.What We OfferOpportunity to influence enterprise-wide AI and analytics ...

seeking a Data Scientist in London to lead GenAI initiatives, building LLM-based applications, prompts, fine-tuning and retrieval augmented generation for enterprise use cases. You will collaborate with data engineers and MLOps, deploy AI workflows via APIs or web apps, and stay ...

responsibly across an organisation.Data, AI & Intelligent Systems Expertise:Strong understanding of modern AI capabilities, including Generative AI, Agentic AI, Retrieval Augmented Generation (RAG), intelligent assistants and AI-enabled automation, and enterprise AI ecosystems such as OpenAI, Google, Anthropic and Microsoft.Experience shaping enterprise AI architectures ...

team.Direct experience with the ML and information retrieval problems underneath modern AI systems, such as embeddings, vector search, retrieval augmented generation, fine-tuning, or agent memory architectures, and the judgement to choose between them for a given problem.Comfort owning both sides ...