251 to 275 of 279 Retrieval-Augmented Generation Jobs in England

enterprise Agentic AI platforms. You will move beyond traditional software QA to build continuous safety pipelines, ensuring our non-deterministic LLM agents, RAG systems, and tool integrations are secure, resilient, and compliant before production release. Key Responsibilities Automated Adversarial Testing: Build and integrate automated red teaming suites into CI/… within FCA, DORA, or EU AI Act frameworks. AWS Bedrock Ecosystem: Hands-on experience configuring, testing, and bypassing Bedrock Guardrails, Agents, and Knowledge Bases (RAG) . AI Security & Fundamentals: Solid understanding of Foundation Models, tool use (function calling), OWASP LLM Top 10 , and NIST AI RMF . Automation Stack: Strong ...

enterprise Agentic AI platforms. You will move beyond traditional software QA to build continuous safety pipelines, ensuring our non-deterministic LLM agents, RAG systems, and tool integrations are secure, resilient, and compliant before production release. Key Responsibilities Automated Adversarial Testing: Build and integrate automated red teaming suites into CI/… within FCA, DORA, or EU AI Act frameworks. AWS Bedrock Ecosystem: Hands-on experience configuring, testing, and bypassing Bedrock Guardrails, Agents, and Knowledge Bases (RAG) . AI Security & Fundamentals: Solid understanding of Foundation Models, tool use (function calling), OWASP LLM Top 10 , and NIST AI RMF . Automation Stack: Strong ...

Development: LLM fine-tuning adapting pretrained LLMs for specific tasks using techniques like parameterefficient fine-tuning (PEFT) (e.g., LoRA, QLoRA). Implementing Retrieval-Augmented Generation pipelines to enhance the knowledge and accuracy of LLMs. Utilizing vector databases for efficient storage and retrieval ...

Skills, and secure API integrations that expose enterprise systems safely to LLM-powered agents. You'll also contribute to agent planning, tool-calling frameworks, RAG architecture, and the broader developer experience for internal AI platform adoption. Key requirements: * Strong Python engineering experience * Experience with LLMs, AI agents, and agentic reasoning … patterns * FastAPI and REST API development * RAG and prompt engineering experience * Kubernetes/containerisation knowledge * Exposure to MCP or similar AI tooling frameworks * Ability to work across platform and product engineering teams This is an opportunity to help shape the future of enterprise AI infrastructure within a large-scale, modern ...

agents and automated decisioning can be embedded into core operations. AI-ready enterprise knowledge architecture - building the structured business meaning required for GenAI, RAG, knowledge graphs, agentic AI, explainable analytics and intelligent process orchestration. This is not a pure data modelling role. It is a business architecture, domain modelling, semantic … simply system-level data structures. 5. Knowledge graph and AI enablement Define insurance entities and relationships for knowledge graphs and graph-based reasoning. Support RAG and GenAI solutions with governed domain knowledge and contextual enrichment. Help define AI agent memory, context, guardrails, decision boundaries, explainability and traceability. Create reusable ontology ...

seeking an exceptional candidate to join our dynamic team as a Principal Research Engineer or Research Fellow to lead the development of next generation technologies and strategies for distributed data sharing and integration of systems. This role focuses on innovative solutions leveraging cloud and edge technologies, enhancing data … tools such as Matlab Simulink (e.g. optimisation and ML toolboxes), PySpark and Jupyter notebooks. Work on projects on areas such as agentic AI, MCP, RAG, generative AI, trust and security, driving innovations from concept through PoC to MVP. Experience with semantic web technologies; RDF, OWL, knowledge graph and ontologies ...

people from £80k to £180k inside a year where the slope has justified it. Polyglot engineers wanted. Go, TypeScript or Python. Deep LLM and RAG integration in user-facing features. Direct line to a founder-led commercial engine reinventing financial infrastructure. About the roles They're hiring top engineers … taste, speed and care. Two seats, same team, distinct flavours. Both roles share the foundation. Stack is Go, TypeScript and Python with LLMs and RAG integrated throughout. You will work directly with Product, Design, and embedded chartered compliance officers and paraplanners. This is not a ticket-processing role. The team ...

rather than purely research-focused individuals. You will work on a broad range of AI challenges spanning multimodal AI, machine learning, computer vision, LLMs, RAG architectures, transformer models, audio processing and intelligent automation features within a highly collaborative engineering environment. Location: Cambridge, UK. Hybrid working model - minimum of 4 days … Kotlin, TypeScript and React, prior experience with these technologies is not required Interest and exposure across AI technologies such as machine learning, LLMs, RAG systems, computer vision, multimodal AI or transformer architectures Ability to work across both research/prototyping and production engineering Strong problem-solving ability and analytical thinking ...

operational software — turning fragmented operational data into structured, trusted intelligence. We're focused on difficult, practical problems: Text-to-SQL against real enterprise schemas RAG over messy operational data Screen recorded workflow mapping Workflow and knowledge tooling that operational teams will actually adopt The platform is being developed alongside … t. Tech you'll touch Laravel · Livewire · Alpine · Tailwind · Python · SQL Server (T-SQL) · PostgreSQL · Power BI/DAX · Docker · GitHub · LLM integrations · RAG · embeddings · Claude Code & Cursor daily Logistics Location: Fully remote, UK Hours: Full-time Type: Contract-to-perm. Outside IR35. Salary: £70,000–£80,000 on conversion ...

scalability, security, and operational readiness. Practical experience with SAP HANA Cloud, SAP AI Core, and Generative AI architectures, including RAG (Retrieval Augmented Generation) frameworks, vector embeddings, and knowledge graph–based approaches. Ability to design scalable AI solutions on SAP BTP that integrate seamlessly with ...

building an enterprise AI platform and are looking for an AI QA Engineer to help define how large scale automated testing operates across a RAG-enabled ecosystem and help ensure their AI platforms are accurate, secure and production ready. You’ll be responsible for validating LLM and RAG-based … quality, hallucinations, security and observability are measured at scale. What you’ll be doing: Designing automated testing strategies for AI/LLM systems Validating RAG pipelines and retrieval accuracy Building frameworks to test AI quality, consistency and performance Measuring and assessing hallucinations and model behaviour Testing AI security ...

value (and where it doesn’t) Use, advise on, and develop AI‐related features such as: Intelligent search/retrieval experiences and RAG Summarisation and document comprehension at scale Context management AI agents, MCP servers, and best‐practice configuration of, for example, AGENTS.md Advanced use of tools such … refactoring support, documentation acceleration, internal workflows) Building products that incorporate AI/LLM features (e.g. assistants/coplots, summarisation, document understanding, semantic search/RAG, extraction, classification, decision support, workflow automation) Strong engineering fundamentals You build with the discipline needed to keep software reliable and maintainable, including: automated testing strategies ...

Banking, Capital Markets, Hedge Funds or Buy-Side Strong grasp of AI capabilities, limitations, and deployment considerations Familiarity with modern AI stacks (e.g. LLMs, RAG, MLOps, cloud platforms) UK-based or UK right-to-work contractors What to expect: Contract opportunities only (inside & outside IR35 depending on client) High-impact … products aligned directly to revenue-generation, decision-making and automation Tier-1 investment banks, buy-side firms, and market-leading financial institutions Roles often released at short notice, hence early engagement is key Interested? If this aligns with your background and you’re open to future UK contract ...

complex financial institutions. Operate as a hands‐on engineer within a squad, taking ownership of defined components and delivering AI capabilities (e.g., agents, RAG pipelines) that meet enterprise standards for reliability, security and observability. Strengthen your foundations through the Applied AI Engineering Academy while taking on more responsibility for solution … business and technology stakeholders; translate requirements into engineering tasks; support workshops, demos and solution reviews; drive adoption through testing and iteration. Design and implement RAG pipelines, agents, microservices and integrations; apply monitoring, evaluation and Responsible AI guardrails. Shape MVP scope, backlog and release planning; capture reusable patterns and contribute ...

company. Requirements Key Responsibilities 1. Data platform evolution Take our current AWS/Snowflake/S3/Postgres setup and enable AI/RAG, product consumption, and multi-tenant access. Work with the Technical Architect to keep this aligned with our event-driven and security model. 2. Data acquisition & ingestion … observable, repeatable, and documented so research and analytics can plug in new sources without rework. 3. AI as a consumption layer Build LLM/RAG endpoints on top of our data and content as a service. Expose these services to Data Insights to enable users to ask, explore, and generate ...

evolve enterprise GenAI and AI architecture patterns Lead design of AI Trust & Controls covering data, prompt, application, and security risks Architect solutions using LLMs, RAG, GenAI, and agentic automation Guide delivery teams and develop reference architectures and pilots Enable LLMOps/AgenticOps (observability, evaluation, governance, lifecycle management) Support integration across … Knowledge of AI governance and risk frameworks (e.g. ISO/IEC 42001, NIST AI RMF, EU AI Act) Hands on experience with GenAI patterns (RAG, agents, orchestration frameworks) Experience with cloud native AI and data platforms (e.g. managed LLMs, ML services, search, analytics) Strong stakeholder engagement across engineering, security, data ...

Founding AI Engineer | Python, LLMs, RAG | VC-Backed PropTech Rebuilding How People Rent and Buy Salary: £100,000 - £120,000 + equity Location: London (Hoxton) – 5 days/week in-office I’m working with a very early-stage AI company that’s taking a proper swing at the property … operations, compliance and transactions through AI agents instead. What They're Looking For Python FastAPI LLMs (production systems) AI agent frameworks (LangGraph or similar) RAG pipelines Postgres Redis Async processing and queuing (Celery, RabbitMQ, SQS) Event-driven architecture CI/CD pipelines What You'll Work With Python backend services ...

client teams to design, build and deploy AI driven solutions on the platform Translate complex research and business questions into production ready LLM and RAG workflows Debug, optimise and scale LLM applications in real world, client facing environments Build and integrate data pipelines and services across cloud platforms and modern … Your Skills and Experience Strong commercial engineering experience in AI, machine learning or data focused roles Hands on experience with retrieval augmented generation and production LLM workflows Confidence debugging and improving end to end LLM systems in live environments Experience working with modern data ...

LLMs, data, APIs, workflows, and systems Stay close to the engineering, not just the architecture Build and guide solutions using Python, Node.js, TypeScript, LLMs, RAG, agents, and integrations Help shape greenfield AI projects from idea through to production Work across client delivery and Conquer’s own AI product development … looking for someone who has: Strong hands-on software engineering experience Experience building real AI, LLM, RAG, agentic, or automation systems Strong backend engineering capability, ideally across Python, Node.js, or TypeScript Comfort working with APIs, data flows, integrations, and enterprise systems The ability to speak clearly with clients and translate ...

already deploying autonomous AI systems into production inside major global enterprises. We’re talking: → AI agents executing workflows end-to-end → Multi-agent systems → RAG + reasoning systems → Real operational impact → Production-grade AI, not demos They’re hiring engineers who can bridge deep technical capability with real-world business … work directly with enterprise customers to design and deploy AI systems that actually do things — not just generate outputs. Ideal backgrounds: LLMs/RAG/MCP/agents applied AI engineering strong Python engineering fundamentals customer-facing or forward deployed experience builders who move fast and like ownership Hybrid London ...

Location Manchester, UK (Hybrid - 3 days per week in office) About ServisBOT ServisBOT is building the next generation of AI-driven enterprise automation for regulated industries — a secure, compliant SaaS platform where AI and humans work together to deliver outcomes our clients can trust. We partner with global … implementation in client environments and ensuring we deliver measurable value. You’ll also build confidence in key AI concepts like prompt engineering, LLMs, and RAG, helping translate customer needs into practical, trustworthy AI-enabled solutions. Key Responsibilities Problem Definition & Discovery Support discovery activities for product initiatives and customer engagements Help ...

Agents, and Denial-of-Wallet-into rigorous test cases. AWS Bedrock Mastery: Overseeing the secure model lifecycle, including the configuration of Guardrails, Knowledge Bases (RAG), and Agentic tool-use. Regulatory Stewardship: Mapping the firm's safeguard catalogue against the specific demands of DORA, FCA Operational Resilience … appetite. Essential Skill Proven track record in UK Financial Services with deep knowledge of FCA compliance and DORA. Solid grasp of Foundation Models (FMs), RAG, and the risks of non-deterministic agentic behavior. Mastery of OWASP LLM Top 10 and the NIST AI Risk Management Framework. Hands-on experience securing ...

Agents, and Denial-of-Wallet-into rigorous test cases. AWS Bedrock Mastery: Overseeing the secure model lifecycle, including the configuration of Guardrails, Knowledge Bases (RAG), and Agentic tool-use. Regulatory Stewardship: Mapping the firm's safeguard catalogue against the specific demands of DORA, FCA Operational Resilience … appetite. Essential Skill Proven track record in UK Financial Services with deep knowledge of FCA compliance and DORA. Solid grasp of Foundation Models (FMs), RAG, and the risks of non-deterministic agentic behavior. Mastery of OWASP LLM Top 10 and the NIST AI Risk Management Framework. Hands-on experience securing ...

reporting, acting as the single point of contact to unblock issues across internal teams, suppliers, and stakeholders. Orchestrate delivery of AI features spanning LLMs, RAG, and multi‐agent workflows from ingestion to inference, including offline/edge constraints where required. Partner with Tech Leads to make trade‐offs in design … delivery across teams using React and Python stacks (e.g., Django, FastAPI, Flask) or equivalent modern frameworks. Hands‐on experience coordinating projects that integrate LLMs, RAG, and related AI components into shipped products. Strong scope, requirements, and budget control; confident discussing technical trade‐offs and reviewing PRs with engineers. Experience ...

opportunity to influence the technical direction of a newly formed AI Lab. Key Responsibilities • Build and deploy production-grade LLM systems • Design and optimise RAG and retrieval workflows • Fine-tune models for tone, style, and output quality • Develop audio-first AI products using TTS/STT workflows • Build … greenfield environment Key Details • Salary: Up to ~£120k base • Working model: Hybrid (3+ days/week in London) • Stack: Python, HuggingFace, LangChain, RAG, multimodal AI, TTS/STT, evaluation frameworks • Sponsorship: To be confirmed Interested? Please apply below. ...