26 to 50 of 83 LLM Jobs in Yorkshire

across digital channels Skills Required: In-depth knowledge of organic search, including technical optimisation, content strategy, off-site and PR Understanding of AI and LLM search optimisation, including how large language models source and cite content, entity-based SEO, structured data, and strategies to improve brand visibility in generative ...

following skill, but don’t worry if you don’t tick the box, we’ll help you develop along the wayAI and LLM experience - you’re comfortable using GenAI tools such as Copilot, Claude or ChatGPT #J-18808-Ljbffr ...

Xpansiv Limited is seeking a QA AI Engineer to test AI-enabled products and the proprietary LLM infrastructure, ensuring quality, reliability, and safety across systems and applications. The role involves creating test plans, executing test cases, building evaluation pipelines, and validating both deterministic software behavior and non-deterministic AI outputs ...

commerce Backend Engineer: AI Native to design, build, and extend backend services powering our modular e‐commerce platform. You will connect personalization, semantic and LLM-enabled search, DAM, PIM, and SAP/HANA integrations, delivering scalable APIs and data flows. The role requires 7+ years in backend/API work ...

operationalize Comply’s semantic layer — turning the ontological models defined by our ontologist and architects into working knowledge graphs, vector search infrastructure, and LLM-powered pipelines. This is a hands-on engineering role at the intersection of knowledge representation, AI infrastructure, and data platform engineering. You will own the delivery … data in vector space Build and operate vector database infrastructure for semantic search and similarity retrieval Implement RAG (Retrieval-Augmented Generation) architectures that ground LLM outputs in Comply’s proprietary data Evaluate and integrate LLM tooling and frameworks appropriate to Comply’s use cases Build reliable, observable data pipelines that ...

Title Machine Learning Engineer Purpose To lead the design and productionisation of Generative AI and LLM-driven applications, utilising GCP and Google’s AI ecosystem. The ML Engineer will architect scalable systems, mentor junior engineers and drive the technical roadmap for integrating Large Language Models into core products, demonstrating innovation … deep learning models and pipelines. 2 Collaborate with cross-functional teams to translate complex business problems into ML-driven solutions. 3 Architect scalable LLM Ops pipelines on GCP (Vertex AI) for model fine-tuning, vector retrieval and low-latency inference. 4 Implement robust LLM evaluation frameworks to monitor output quality ...

Xpansiv is seeking a QA AI Engineer to ensure the quality, reliability, and safety of AI-driven products and LLM infrastructure. You will design test plans, execute cases, and build evaluation pipelines in a cross-functional environment. You will work with AI engineering, product, operations, and business stakeholders to embed ...

design, build, and expand the backend services powering our modular e-commerce platform. You will work on APIs, data flows, and integrations with personalization, LLM‐driven search, DAM and PIM systems, with an AI‐native development mindset. You will pair with cross‐functional teams, ensuring code quality, security, and performance ...

Backend Engineer with AI-native expertise to design and extend the company’s modular e-commerce backend. You will connect core capabilities like personalization, LLM-driven search, DAM, PIM, and SAP/HANA, building APIs and data flows for scalable, secure systems. The role emphasizes AI-assisted development, strong engineering ...

customer-focused content. Partner with Sales, Marketing and Technical SMEs to ensure content is accurate, relevant and commercially impactful. Drive SEO and AI/LLM content optimisation using performance insights and best practice. Establish content standards, governance and best practice across the wider team. Collaborate with external agencies and partners ...

solutions that power AI-driven case management capabilities. Build, implement and optimise data pipelines that connect enterprise applications and systems with AI and large language model platforms. Create, refine and optimise prompts and AI workflows to improve the quality, accuracy and relevance of AI-generated outputs. Support and drive … work independently, take ownership of technical initiatives and provide leadership within a multidisciplinary team. Additional Skills & Qualifications experience with Gemini or other large language model platforms. experience working with Google Cloud Platform (GCP). Hands-on experience in agentic AI development and orchestrating agent-based workflows. Knowledge of AI-assisted ...

hands-on Agentic AI engineering in Financial Crime Riskdriving end-to-end, production-grade AI solutions from governance and senior decision-making through to LLM/agent workflow design, evaluation, observability, and hypercare, ensuring solutions are adopted in investigations and meet regulated-bank standards. As our client employee … production-grade AI and Agentic AI solutions for financial crime risk detection and investigation -Contribute to solution design and build where needed, including: LLM/agent workflow design (tool use, orchestration, guardrails, human-in-the-loop patterns) API/service integration into alerting, case management, and investigator workflows -Evaluation harnesses ...

platform and turn successful approaches into reusable tools and accelerators. What you'll be working on: Building AI solutions using RAG, AI agents, LLM integrations and MCP Taking solutions from prototype through to production, including security, scalability, guardrails and observability Building AI evaluation and testing frameworks to measure accuracy … TypeScript or similar, with experience across multiple modern languages Full-stack capability, including back-end and data engineering Proven experience building and shipping production LLM/AI applications Hands-on experience with RAG, AI agents, prompt engineering, tool orchestration and MCP Experience with AI evaluation, testing, datasets and guardrails Client ...

We recognise our people are the best thing about Red Badger and that a truly diverse workplace where people are free to be themselves is essential for great culture and great outcomes. If you like ...

protocols (MQTT, OPC-UA). Desirable Desirable Interview/Application Familiarity with semantic web technologies (RDF, SPARQL), linked data principles, or large language model (LLM) APIs and agentic frameworks for automated data integration. Further Information Grade 7 Salary £38,784 - £47,289 per annum. Work arrangement Full-time Duration Fixed ...

Finance AI platform. This hands-on leadership role focuses on scalable engineering patterns, accelerating delivery, and mentoring development teams. You will design and oversee LLM, RAG, and Agentic AI integrations across Azure, AWS, and GCP, collaborate with architects to ensure secure, maintainable solutions, and set standards for observability, governance ...

step workflows using loops, branching, routing, tool use, state management, retries and human-in-the-loop controls. Evaluation: Using regression sweeps, canary testing and LLM-as-judge scoring to determine what is ready to ship. ML infrastructure: Building versioned training pipelines, model registries, scheduled jobs and deployments using Azure ML. … experience designing, building and optimising agentic systems, particularly graph-based and iterative workflows involving loops, branching, routing, tool use and state management. Experience evaluating LLM applications using approaches such as gold datasets, regression testing, LLM-as-judge scoring and canary testing. Experience with cloud ML platforms - ideally Azure ML, Functions ...

embeddings/vector search, tool calling, agent architecture, evaluation, grounding, orchestration. Architect and govern the Enterprise Agentic AI Strategy, deploying multi-agent frameworks and LLM-powered tools at scale. Architect and deploy enterprise-grade multi-agent AI systems for complex, multi-step workflows, integrating with ERP, CRM, and ITSM … automate high-value decisions end-to-end. Design internal AI tools and agents (e.g., AI Finance Bot, domain-specific LLM applications) and lead the roadmap for next-generation agentic platforms as emerging capabilities mature. Drive Data Governance & AI Readiness – quality, lineage, observability, catalog, access controls, PII, retention, AI data governance. ...

About the role At Parallax, we celebrate the curious. The people who love getting stuck into tough challenges, understanding what really matters and using technology to create meaningful outcomes. We’re looking for a Senior ...

stack services (frontends and backend services) into production environments. End-to-End GenAI Development: Build comprehensive GenAI features including backend API services, custom tools, LLM model integration, and evaluation harnesses. AI Agents & MCP Integration: Design, build, and maintain Model Context Protocol (MCP) servers and services that securely expose backend data … full stack, guiding the development of responsive frontend applications (React/TypeScript) and robust, scalable backend services (Python, Java, Kotlin, or Node.js). LLM Observability & Reliability: Establish robust LLM observability, evaluations, and caching, implementing latency optimisations and comprehensive monitoring (logging, usage tracking, agent behaviour). Operational Excellence: Champion high availability ...

businesses to thrive and economies to prosper, and, ultimately, helping people fulfil their hopes and realise their ambitions. We are seeking a MLOps Engineer (LLM/GenAI) In this fantastic role, you’ll engineer production-grade infrastructure for modern AI: hosting LLMs and speech/embedding models, pushing inference performance … Optimise inference for latency, throughput, and cost (e.g., quantisation, KV-cache optimisation, dynamic/continuous batching) Evaluate and integrate inference frameworks (e.g., vLLM, TensorRT-LLM, SGLang) to maximise performance on target hardware Own inference health/performance monitoring (latency, throughput, TTFT, memory, availability) and troubleshoot bottlenecks/deployment issues Build ...

products developed by Xpansiv. This role is responsible for ensuring the quality, reliability, accuracy, and safety of Xpansiv’s AI-driven products and proprietary LLM infrastructure. The QA AI Engineer will create test plans, document and execute test cases, build automated and semi-automated evaluation frameworks, and validate both deterministic … business lines Develop evaluation datasets, golden sets, and scenario suites that measure accuracy, consistency, structured-output quality, policy adherence, and business-rule compliance of LLM outputs Detect, document, and reproduce AI-specific failure modes, including hallucinations, prompt injection, inconsistent outputs, formatting errors, data leakage, bias, unsafe responses, and model ...

Protect Group specialises in enhancing customer experience and generating additional revenue for businesses through innovative technology solutions. Founded in 2016, we’ve rapidly grown to serve over 400 business partners across 75+ countries, with a ...

standards, reusable patterns and guardrails for building reliable, secure and supportable automations. The role increasingly draws AI into workflows as a step, such as LLM calls to classify, extract or summarise, working in close partnership with the AI Engineering team, which owns agents, LLM-powered applications, prompt engineering, evaluations … designed, tested, deployed, monitored and supported, including error handling, version control, environment separation and observability. Embed AI as steps within workflows, such as LLM calls to classify, extract or summarise, consuming capabilities and patterns provided by the AI Engineering team, and preferring deterministic automation where it is safer, simpler ...

Leeds, United Kingdom | Posted on 02/25/2026 Responsibilities Design, develop, and maintain Copilot agents, plugins, connectors, and LLM workflows in Copilot Studio Build scalable components: prompt orchestration, retrieval layers, Power Automate flows, model interfaces, validation pipelines Develop and optimise RAG components - embeddings, vector queries, metadata strategies … Microsoft Graph, APIs, and Power Platform connectors Implement secure-by-design and responsible AI practices: guardrails, controls, monitoring, auditability Build observability: logging, telemetry, and LLM monitoring for quality and incident triage Create reusable assets - prompt libraries, agent templates, connectors, test harnesses, and documentation Conduct rapid prototyping to validate feasibility, model ...