176 to 200 of 2,345 LLM Jobs in England

patterns for junior engineers Requirements Commercial experience building multi-agent or agentic AI systems in production Strong Python skills and hands‐on experience with LLM frameworks (LangGraph, LangChain, Haystack, or similar) Experience deploying AI/ML systems into production environments Familiarity with Docker, Git, and cloud platforms (AWS preferred) Understanding ...

experience:Build, test, and deploy AI and machine learning components within client projects to the standards and designs set by senior colleagues.Develop GenAI and LLM-based features (prompting, retrieval-augmented generation, and simple agentic workflows) alongside more traditional ML models.Deliver classical data science tasks (data preparation, feature engineering, model training ...

processing frameworks Systems‐Level Programming: Experience with low-level systems programming such as storage systems, Kubernetes operators, OS-level software development, or daemon services (llm‐d, system agents) ML Platform Engineering: Experience productionizing ML pipelines, batch job orchestration, model fine‐tuning workflows, and Jupyter notebook orchestration systems Enterprise Deployment: Experience ...

large‐scale consumer applications Previous experience as a site lead, office lead, or similar multi‐team leadership role Background in building infrastructure for LLM training or inference Contributions to open‐source infrastructure or AI infrastructure projects Experience scaling teams from 0 to 20+ engineers Active involvement in the London ...

role: The Search and AI Platform is Elsevier’s agentic data platform, which powers products such as Scopus, ScienceDirect, and our next-generation LLM-powered research systems. The platform utilises agentic services to interrogate our rich knowledge graphs, search and recommendation systems, and our unparalleled collection of research data, delivering ...

stakeholders Your Skills Software engineering experience while leading engineering teams Strong hands‐on experience building and deploying AI applications in production Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns Experience with agentic frameworks and autonomous agent architectures Proficiency in Python and modern software development practices (testing, code ...

programmes, including review boards, guardrails, standards, and alignment to delivery, regulatory, and audit requirements.Agentic and AI-enabled architecture: Lead designs that incorporate GenAI and LLM platforms for example Claude, OpenAI, Gemini or equivalent alongside agent orchestration and tool use and design scalable AI and ML solutions aligned to business goals ...

developer platforms, internal tooling, shared services, or infrastructure that supports multiple engineering teams. Hands-on experience building AI-powered applications and services using modern LLM frameworks and agentic architectures. Good understanding of modern AI concepts and practices, including: Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Prompt Engineering AI Guardrails ...

Azure, leveraging core technologies in the AI Foundry ecosystem, understanding different business challenges require varied solutions from SLM's to intelligent Agentic automation from LLM foundational models, Human in the Loop and MLOps. Data Architecture Design: You understand and know when to use the following data architecture design patterns ...

context.Strong product sense and commercial instinct - you can connect work to P&L outcomes and defend value trade-offs.Active practitioner of applied AI/LLM tooling in your analytics or prototyping workflow.Excellent storytelling - credible into senior commercial stakeholders.It would also be greatifyou have:Familiarity with AI evaluation patterns - eval sets ...

Azure, leveraging core technologies in the AI Foundry ecosystem, understanding different business challenges require varied solutions from SLM’s to intelligent Agentic automation from LLM foundational models, Human in the Loop and MLOps.Data Architecture Design: You understand and know when to use the following data architecture design patterns RAG (Retrieval ...

modern engineering practices such as Docker-based workflows and infrastructure as code.Practical understanding of AI-enabled engineering and product use cases, including common LLM concepts and considerations such as privacy, security, bias, governance, and cost.Clear communication skills, with the ability to work effectively with engineers, product managers, and senior stakeholders.A ...

frameworks, or architectural playbooks — at scale.Fluency across the modern data and AI stack: cloud data platforms (Snowflake, Databricks, BigQuery), agentic frameworks, RAG, vector databases, LLM orchestration, data governance, and enterprise integration patterns.Experience with prompt engineering, agent lifecycle management, and hands-on prototype development.Hands-on proficiency in programming (e.g., Python, JavaScript ...

modelling, integration patterns, event-driven design, canonical semantic layers. Exposure to AI/ML data requirements and the data modelling implications of analytics and LLM-enabled use cases in asset management. Certifications: DAMA/CDMP, TOGAF, or cloud data certifications (Snowflake SnowPro, Azure/AWS/GCP equivalents). Experience ...

Proven experience building complex AI systems, with hands‐on expertise in Retrieval‐Augmented Generation (RAG) and AI Agent architectures. Deep, hands‐on experience with LLM APIs and/or fine‐tuning and serving open‐source models. Strong understanding of prompt engineering and context engineering to maximize model relevance and accuracy. ...

related technical field OR Bachelor's Degree in Computer Science or related technical field OR equivalent experience. Experience designing, deploying, and operating AI or LLM-based solutions, including prompt engineering, retrieval-augmented approaches, model tuning, evaluation, data quality, performance monitoring, and use of cloud AI platforms Familiarity with deploying ...

digital future of fintech transactions and ensuring a reliability of 99.9999% and beyond. \n \n \n Build Agentic Solutions using world's most advanced LLM models from Anthropic, OpenAI and others \n \n Build Deep Learning solutions using AI/ML Platforms for real time transactions at a scale ...

ensuring a reliability of 99.9999% and beyond. \n \n The Work itself: \n \n \n Build Agentic Solutions using world's most advanced LLM models from Anthropic, OpenAI and others \n \n Build Deep Learning solutions using AI/ML Platforms for real time transactions at a scale of 100K+ ...

complex architectural risks into clear, concise, and actionable strategic plans for senior executive leadership and non-security stakeholders.Nice to have:AI/ML Pipeline & LLM Familiarity: Hands-on experience or deep architectural familiarity with securing ML training lifecycles, protecting proprietary model weights, or building guardrails for autonomous workflows.Regulated Data & Compliance ...

. This role will support a growing portfolio of AI initiatives across the organization, focusing on building scalable, secure, and well-governed solutions, including LLM-powered agents, multi-agent systems, retrieval-augmented generation (RAG), and intelligent automation platforms.You will work closely with data scientists, engineers, enterprise architects, and business stakeholders ...

compliance operations — secrets management, IAM/least privilege, PCI DSS-aligned controls, auditability.Reliability engineering — SLIs/SLOs, incident management, cost and capacity management (incl. LLM token/credit cost control).Nice‐to‐have skillsLLMOps/MLOps — model serving, gateway/proxy management, prompt/version management, guardrails at runtime.Experience hosting ...

operations — secrets management, IAM/least privilege, PCI DSS-aligned controls, auditability.* Reliability engineering — SLIs/SLOs, incident management, cost and capacity management (incl. LLM token/credit cost control).**Nice‐to‐have skills*** LLMOps/MLOps — model serving, gateway/proxy management, prompt/version management, guardrails ...

based product portfolio. Partner with product managers, content managers, and senior stakeholders to design, build, deploy, and optimise state of the art AI, ML, LLM, and GenAI solutions. Use AI to broaden reach, engagement, and utilisation across our services. Identify opportunities to drive efficiency through AI across the wider business. ...

audit standards Champion scalable, secure, and efficient AI implementation. What We're Looking For Core Skills & Experience Strong experience in AI Engineering, ML/LLM applications, or intelligent automation Solid Java engineering background with production-quality coding practices Experience with CI/CD tools e.g., Jenkins, GitLab CI Hands ...

EventBridge or Secrets Manager. Big data technologies including DuckDB, pandas, Spark, Databricks or Snowflake. AI/ML technologies including vector databases, semantic search or LLM orchestration frameworks. Continuous delivery and modern development workflows. Data science applications or financial data visualisation. What We Offer The opportunity to work on technically challenging ...