1 to 25 of 669 LLM Jobs in England

databases (SQL and NoSQL) and data modeling Knowledge of vector databases and embeddings for AI applications Strong understanding of machine learning fundamentals and LLM capabilities/limitations Experience building and deploying AI/ML systems in production environments Familiarity with MLOps practices including model deployment, monitoring, and lifecycle management Understanding ...

. Experience with Power BI, Tableau, KNIME or Python visualisation frameworks . Familiarity with modern cloud platforms (Azure, AWS, GCP, Snowflake, Databricks). GenAI & LLM Fluency Practical experience using large language models via APIs (e.g. OpenAI, Azure OpenAI, Anthropic). Structured prompt engineering , including templates, guardrails and basic evaluation approaches. ...

business impact and a strong programming foundation (Java, Python, Go, or equivalent). Hands‐on experience with AI/ML engineering — including working with LLM APIs (OpenAI, Anthropic, Gemini, or open‐source equivalents), embedding models, and vector databases. Proven expertise in prompt engineering : designing, iterating, and evaluating prompts for production ...

enhancement. The Role * Design and develop production-grade AI applications using both traditional Machine Learning and Generative AI approaches* Build and deploy RAG systems, LLM-powered applications and agentic workflows* Develop scalable APIs, microservices and cloud-native AI solutions* Work closely with business stakeholders to translate requirements into technical solutions ...

business stakeholders Required Background & Skills Strong software engineering background with backend development expertise Strong Python experience and cloud-native development Experience integrating AI/LLM technologies into real-world applications Experience building scalable production systems Understanding of APIs, distributed systems, microservices, and system design Experience with cloud platforms such ...

platforms for downstream data consumption, operational analytics and decision support. Experience architecting AI/ML and agentic automation solutions within trading technology estates, including LLM integration, RAG patterns, intelligent scheduling and predictive analytics. Familiarity with Agile/SAFe delivery frameworks at scale, with experience embedding architecture governance into sprint-based ...

Senior AI Engineer/AI Engineering Consultant/Generative AI Consultant/Senior Machine Learning Engineer/AI & ML Consultant/MLOps Engineer/LLM Engineer/AI Engineering Consultant/Senior AI Engineer/Generative AI Engineer/AI Solutions Architect/Data & AI Consultant/AI Solutions Consultant ...

Python development skills and deep experience with modern AI/ML frameworks and SDKs. Proven experience designing and deploying production-grade RAG solutions and LLM-powered applications. Strong experience building and deploying AI agents, orchestration frameworks, and automated workflows. Experience with Azure AI Services, Azure OpenAI, Azure Machine Learning ...

outcome-based KPIs. Platform & Architecture (Python Full-Stack) Architect and deliver reusable Python platforms (backend), ReAct/Vue (frontend) and reference services for: LLM, RAG/GraphRAG services, agent orchestration, prompt/version management, evaluation-as-code, guardrails, and content moderation. Data engineering, feature/vector stores; retrieval pipelines; Text ...

Expertise: Proven experience developing and deploying intelligent conversational AI systems using RAG architectures, Model Context Protocol (MCP), AI-enabled search, vector databases, and LLM integration. Frameworks: Hands-on experience building GenAI applications using LangChain and LangGraph (agent architecture design, state management, and graph-based workflow orchestration). ML & Cloud Ecosystems ...

communication skills, both with teams and in client-facing engagements Interested in building AI applications, ranging from forecasting tools to image recognition applications and LLM-based chatbots and agents Proven ability to build machine learning models and pipelines using Python and common ML and DL libraries (e.g. Pytorch, Tensorflow) from ...

platforms, leveraging third‐party capabilities where they add value that minimise vendor lock‐in and support rapid experimentation across Azure OpenAI and alternative LLM ecosystems. You’ll also shape the design of agentic AI systems, orchestration layers, and integration patterns that support flexible, production‐ready AI solutions at pace. Working ...

automated evaluation systems such as LLMasJudge and hybrid scoring approaches. based testing, regression suites, multi turn agent simulations, and automated evaluation systems such as LLM as Judge and hybrid scoring approaches/li , li Build, refine, and maintain frameworks that assess model quality, robustness, performance, safety, explainability, and reliability ...

extending to Manchester. Since 2017, we’ve been delivering AI systems at scale – from ranking models and savings optimization engines to client‐facing LLM‐powered experiences used by business travelers worldwide. We are looking for a Machine Learning Engineer II to join our Product AI Engineering team. You will help ...

deployment approaches Drive high-quality engineering practices across testing, deployment, monitoring, and optimisation Tech environment Key technologies include: Python Azure Databricks Generative AI/LLM frameworks Agentic AI tooling and orchestration frameworks LangChain/LangGraph PyTorch and ML libraries REST APIs Docker and containerisation CI/CD pipelines Git-based ...

across digital sports media platforms. * Collaborate with product, data, and engineering teams to deliver AI-driven features and audience engagement tools. * Build and optimise LLM-powered applications, recommendation systems, and intelligent content workflows. * Develop and maintain robust data pipelines and model deployment infrastructure. * Implement monitoring, evaluation, and governance processes ...

like Node.js, Python and TypeScript. AI Tooling & Ecosystems: Proven experience or strong understanding of AI development tools (like Claude Code), Model Context Protocol (MCP), LLM integration and prompt engineering. Cloud & DevOps: Hands‐on experience with cloud platforms (GCP, AWS), containerization (Docker, Kubernetes) and modern CI/CD practices. Frontend Development ...

systems Proven delivery across at least two of: Azure AI Foundry, Databricks, AWS (all three ideal) Deep expertise in GenAI, agentic AI, RAG patterns, LLM fine-tuning, and vector databases Strong Python foundations — PyTorch, Transformers, FastAPI, LangChain/LangGraph Experience with MLOps, CI/CD, IaC, and container orchestration ...

AI Engineer Location: London (Hybrid - 2-3 days per week onsite) Salary: £80,000 - £120,000 + Benefits Type: Permanent About 167 Solutions 167 Solutions is a specialist technology recruitment consultancy connecting organisations with exceptional ...

AI Engineer Location: London (Hybrid - 2-3 days per week onsite) Salary: £80,000 - £120,000 + Benefits Type: Permanent About 167 Solutions 167 Solutions is a specialist technology recruitment consultancy connecting organisations with exceptional ...

maintain analytical models using Python, SQL and cloud-based data platforms • Apply machine learning, AI and statistical techniques to business challenges • Work with NLP, LLM and Generative AI technologies where appropriate • Validate data, perform testing and ensure analytical output quality • Monitor model performance and support ongoing optimisation and governance • Contribute ...

technology architecture, 3–5 years focused on AI/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 ...

engineering domains. End-to-end exposure in model lifecycle development, including extensive experience training and deploying ML models in production environments. Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns. Experience in fine-tuning LLMs for domain-specific enterprise applications. Strong expertise in MLOps and LLMOps, ensuring scalable ...

candidates will bring most — not necessarily all — of the following:AI and engineering depthHands-on experience building and shipping production AI systems — agentic frameworks, LLM applications, RAG systems, computer vision, or applied ML pipelines.Solid full-stack foundation (Python, JavaScript/TypeScript, and modern frameworks) with the technical credibility to engage ...

Strong communication skills and the ability to work effectively across engineering, product and data teams Nice-to-haves Experience supporting computer vision, deep learning, LLM or other compute-intensive ML workloads Experience with GPU infrastructure, distributed training or high-performance compute environments Familiarity with feature stores, model registries and automated ...