26 to 50 of 2,799 LLM Jobs in England

Cost Controls.* Software Engineering: Clean Code (SOLID, DRY), DDD, modular architecture, TDD, code quality tools. · AI Engineering (Desirable): RAG pipelines, agentic workflows, MCP, LLM integration (OpenAI, Gemini or other models from Huggingface), LangSmith, TruLens.* Agentic Frameworks (Desirable): LangChain, CrewAI, Autogen, OpenAI Agents, Google ADK.## **WHAT YOU'LL LOVE ABOUT WORKING ...

Cost Controls.* Software Engineering: Clean Code (SOLID, DRY), DDD, modular architecture, TDD, code quality tools. · AI Engineering (Desirable): RAG pipelines, agentic workflows, MCP, LLM integration (OpenAI, Gemini or other models from Huggingface), LangSmith, TruLens.* Agentic Frameworks (Desirable): LangChain, CrewAI, Autogen, OpenAI Agents, Google ADK.## **WHAT YOU'LL LOVE ABOUT WORKING ...

Large Language Model (LLM) Technology Architect Career Level: Associate Manager/Specialist Location: London YOU ARE As a hands-on AI/LLM Architect, you will be at the heart of designing and building advanced AI systems that power the modern enterprise. This is a deeply technical, hands-on role … enterprise grade advanced ai solutions using agentic, generative and classical AI/ML using at least one cloud vendor. Practical experience in the Agentic, LLM and Generative AI space. Well versed in coding using python Solid foundation in architecting and operationalizing LLM driven application architecture patterns. Professional working experience ...

will be responsible for guiding a team of AI Engineers in the design, development, deployment, and operation of scalable AI and Large Language Model (LLM) powered applications. Working closely with Data Scientists, Product teams, and business stakeholders, you will ensure AI products are secure, reliable, and built to enterprise standards. … performing technical teams, creating a culture of collaboration, innovation, continuous improvement, and professional growth. Hands‐on experience designing, building, and deploying Large Language Model (LLM) powered solutions and generative AI applications at enterprise scale. Strong Python development skills, with experience using machine learning frameworks such as PyTorch, TensorFlow, and Scikit ...

will be responsible for guiding a team of AI Engineers in the design, development, deployment, and operation of scalable AI and Large Language Model (LLM) powered applications. Working closely with Data Scientists, Product teams, and business stakeholders, you will ensure AI products are secure, reliable, and built to enterprise standards.Reporting … performing technical teams, creating a culture of collaboration, innovation, continuous improvement, and professional growth.* Hands-on experience designing, building, and deploying Large Language Model (LLM) powered solutions and generative AI applications at enterprise scale.* Strong Python development skills, with experience using machine learning frameworks such as PyTorch, TensorFlow, and Scikit ...

advanced AI and machine learning solutions. Build, train, validate, and optimize machine learning and deep learning models. Develop Generative AI and Large Language Model (LLM) applications. Create AI-driven automation, analytics, and decision-support solutions. Design scalable data pipelines for AI and machine learning workloads. Develop APIs and software integrations ...

will lead AI initiatives, design experimentation frameworks, and provide technical leadership across multimodal AI projects. Key Responsibilities: Lead research and development activities across LLM, VLM, and multimodal AI domains. Design, implement, and evaluate AI models incorporating text, image, and multimodal reasoning capabilities. Develop and optimise Retrieval-Augmented Generation (RAG) architectures. ...

intersection of Data Engineering, AI and Generative AI , giving you the opportunity to work across modern data platforms, scalable data pipelines, machine learning and LLM-enabled solutions.You must currently come from, or have recent experience working within, a consultancy or professional services environment , with experience delivering technical solutions directly ...

products live in production and used by paying clients, ideally in a regulated environment. Hands-on knowledge of the Generative AI product lifecycle, including LLM selection, prompt design, retrieval-augmented generation, evaluation, guardrails, and managing cost, latency and reliability at scale. Strong commercial acumen, with experience of building business cases ...

know yet). You’ll cover: Foundations of machine learning AI literacy Ensemble methods & model optimisation Databases & big data Neural networks & deep learning LLM foundations, engineering, customisation and integration Generative and Agentic AI MLOps & cloud computing Your personal learning plan could include Up to three Stanford Artificial Intelligence Professional Programmes ...

know yet). You'll cover: Foundations of machine learning AI literacy Ensemble methods & model optimisation Databases & big data Neural networks & deep learning LLM foundations, engineering, customisation and integration Generative and Agentic AI MLOps & cloud computing It's all live lectures, tutor-led group work and real-world challenges from ...

know yet). You'll cover: Foundations of machine learning AI literacy Ensemble methods & model optimisation Databases & big data Neural networks & deep learning LLM foundations, engineering, customisation and integration Generative and Agentic AI MLOps & cloud computing It's all live lectures, tutor-led group work and real-world challenges from ...

Generative AI solutions in production environments. Demonstrable experience successfully designing and launching multiple enterprise GenAI implementations beyond proof‐of‐concept stage. Strong expertise in LLM ecosystems including OpenAI, Anthropic, Gemini, and related model platforms. Hands‐on experience with RAG architectures, Agentic AI frameworks, and orchestration tools such as LangChain, LangGraph ...

generative AI or agentic AI solutions. Strong hands-on software engineering experience using Python, APIs and cloud-native design patterns. Deep understanding of large language model applications, including orchestration, tool use, grounding, retrieval-augmented generation, structured outputs, context management and evaluation. Experience designing multi-step or multi-agent workflows ...

learning solutions. Work closely with stakeholders to understand business challenges and translate them into scalable data products. Develop and improve AI-powered solutions, including LLM and automation use cases. Drive best practices in model development, testing, monitoring and governance. Mentor colleagues and contribute to the wider technical direction ...

solutions using Microsoft Foundry, Azure OpenAI, Azure AI Search, Azure Machine Learning and Azure services. Design and implement RAG, vector search, AI agents and LLM-based applications. Integrate AI solutions with enterprise data, applications and APIs. Establish AI engineering, security, governance, monitoring and responsible AI practices. Lead technical teams ...

adoption. Must-Haves Candidates must meet the following minimum criteria: Experience: 4+ years in software, data, or ML engineering, including 2+ years building production LLM apps, RAG, or autonomous agents. Python: Expert-level production Python (FastAPI, Pydantic, asyncio, pytest, packaging). Agentic Frameworks: Hands-on experience with frameworks such ...

pipelines.Support LLMOps practices: prompt and model versioning, automated evaluation, deployment pipelines and observability for AI workloads in production.Your Skills and ExperienceProduction experience building LLM-based applications on Azure that went live and that you then supported, rather than proofs of concept that stopped at demo.Strong production coding in Python ...

LLMOps practices: prompt and model versioning, automated evaluation, deployment pipelines and observability for AI workloads in production. Your Skills and Experience Production experience building LLM-based applications on Azure that went live and that you then supported, rather than proofs of concept that stopped at demo. Strong production coding ...

following: Data modelling experience including dimensional design, medallion architecture or source-to-target mapping Hands-on experience building pipelines that support agentic workflows or LLM-based applications Familiarity with data product principles: discoverability, reusability, quality contracts and SLAs Hands-on experience with Decision Intelligence Platforms (e.g. Palantir, Quantexa) Infrastructure ...

following: Data modelling experience including dimensional design, medallion architecture or source-to-target mapping Hands-on experience building pipelines that support agentic workflows or LLM-based applications Familiarity with data product principles: discoverability, reusability, quality contracts and SLAs Hands-on experience with Decision Intelligence Platforms (e.g. Palantir, Quantexa) Infrastructure ...

Experience Data modelling experience including dimensional design, medallion architecture or source‐to‐target mapping Hands‐on experience building pipelines that support agentic workflows or LLM‐based applications Familiarity with data product principles: discoverability, reusability, quality contracts and SLAs Hands‐on experience with Decision Intelligence Platforms (e.g. Palantir, Quantexa) Infrastructure ...

Bash); C# or Go a plus. Experience deploying and supporting AI, machine learning, API, and cloud application workloads in production environments. Experience operating LLM-based workloads in production, including multi-provider routing, capacity and quota management, rate limiting, streaming and asynchronous job patterns, retries and backpressure, cost attribution ...

taking AI prototypes to production in enterprise environments. Education: BS in Engineering, Computer Science or equivalent; advanced degree preferred. Agentic AI/LLMs: LLM orchestration, prompt engineering, context-window management and production guardrails; MCP, tool-augmented agents and RAG at enterprise scale. Enterprise integration: Integrating AI into enterprise systems ...

other relevant enterprise platforms. Understand the foundations required for safe and scalable AI delivery, including identity, permissions, environments, data lineage, observability, evaluation, auditability, LLM access patterns and responsible AI controls. Work closely with Data Solutions & Architecture colleagues to ensure AI use cases are built on the right data foundations. Understand ...