951 to 975 of 1,587 LLM Jobs in England

Senior Software/Platform Engineer (LLM/AI Interest) Brand new AI Platform £120,000 - £130,000 London - 4 days a week in office (Paddington) Python, GCP, Kubernetes, Terraform, CI/CD, AI/LLM exposure/interest Here at Burns Sheehan, we re working with a leading UK tech business in the payments and financial services space … at scale. Automating infrastructure/model deployments using Kubernetes, Terraform, and CI/CD pipelines. Building and managing vector databases and retrieval systems to support RAG pipelines. Working with LLM frameworks like LangChain , LangGraph , CrewAI , or similar tools. Partnering closely with engineering, security, and product teams to deliver safe, production-ready AI systems. What They re Looking For: Strong background … Python, Java or Go. Experience with Kubernetes, Terraform, and cloud environments (GCP preferred). Understanding of microservices, distributed systems, and cloud-native architecture. Interest or experience in AI infrastructure, LLM tooling, or AI platform enablement. A collaborative engineer who enjoys problem-solving and contributing to technical direction. If you re interested in helping build real AI infrastructure within a fast More ❯

and ship agent workflows in Python Write excellent prompts and structured output schemas (JSON/JSON‐Schema, Pydantic) that are robust across models and providers. Integrate and operate multiple LLM providers (OpenAI primarily, also Anthropic and Google today, evaluate Groq/Cerebras and others for cost/latency/perf). Build observability for LLM calls: tracing, logging, cost accounting … to validate outputs with users, and iterate quickly. Our current/target stack (you don't need all of this) Python: 3.12+, FastAPI, Pydantic, asyncio/httpx, pytest, mypy LLM orchestration & evals: OpenAI/Anthropic/Gemini; Orq.ai and LangSmith are in use today (nice‐to‐have, not required); experience with lightweight, framework‐agnostic patterns is valued. Data & infra: SQL … RAG, Guardrails/Outlines/Instructor. Vector DBs, embeddings, and data pipelines. First 90 days - example outcomes Review and improve existing core Agentic workflows Improve the quality of existing LLM outputs through prompting Introduce auto Value Proposition feature to production Review and reduce costs of existing pipelines by at-least 50% Why join Evergrowth Direct impact and ownership: report to More ❯

and ship agent workflows in Python Write excellent prompts and structured output schemas (JSON/JSON‐Schema, Pydantic) that are robust across models and providers. Integrate and operate multiple LLM providers (OpenAI primarily, also Anthropic and Google today, evaluate Groq/Cerebras and others for cost/latency/perf). Build observability for LLM calls: tracing, logging, cost accounting … to validate outputs with users, and iterate quickly. Our current/target stack (you don't need all of this) Python: 3.12+, FastAPI, Pydantic, asyncio/httpx, pytest, mypy LLM orchestration & evals: OpenAI/Anthropic/Gemini; Orq.ai and LangSmith are in use today (nice‐to‐have, not required); experience with lightweight, framework‐agnostic patterns is valued. Data & infra: SQL … RAG, Guardrails/Outlines/Instructor. Vector DBs, embeddings, and data pipelines. First 90 days - example outcomes Review and improve existing core Agentic workflows Improve the quality of existing LLM outputs through prompting Introduce auto Value Proposition feature to production Review and reduce costs of existing pipelines by at-least 50% Why join Evergrowth Direct impact and ownership: report to More ❯

and ship agent workflows in Python Write excellent prompts and structured output schemas (JSON/JSON‐Schema, Pydantic) that are robust across models and providers. Integrate and operate multiple LLM providers (OpenAI primarily, also Anthropic and Google today, evaluate Groq/Cerebras and others for cost/latency/perf). Build observability for LLM calls: tracing, logging, cost accounting … to validate outputs with users, and iterate quickly. Our current/target stack (you don't need all of this) Python: 3.12+, FastAPI, Pydantic, asyncio/httpx, pytest, mypy LLM orchestration & evals: OpenAI/Anthropic/Gemini; Orq.ai and LangSmith are in use today (nice‐to‐have, not required); experience with lightweight, framework‐agnostic patterns is valued. Data & infra: SQL … RAG, Guardrails/Outlines/Instructor. Vector DBs, embeddings, and data pipelines. First 90 days - example outcomes Review and improve existing core Agentic workflows Improve the quality of existing LLM outputs through prompting Introduce auto Value Proposition feature to production Review and reduce costs of existing pipelines by at-least 50% Why join Evergrowth Direct impact and ownership: report to More ❯

and ship agent workflows in Python Write excellent prompts and structured output schemas (JSON/JSON‐Schema, Pydantic) that are robust across models and providers. Integrate and operate multiple LLM providers (OpenAI primarily, also Anthropic and Google today, evaluate Groq/Cerebras and others for cost/latency/perf). Build observability for LLM calls: tracing, logging, cost accounting … to validate outputs with users, and iterate quickly. Our current/target stack (you don't need all of this) Python: 3.12+, FastAPI, Pydantic, asyncio/httpx, pytest, mypy LLM orchestration & evals: OpenAI/Anthropic/Gemini; Orq.ai and LangSmith are in use today (nice‐to‐have, not required); experience with lightweight, framework‐agnostic patterns is valued. Data & infra: SQL … RAG, Guardrails/Outlines/Instructor. Vector DBs, embeddings, and data pipelines. First 90 days - example outcomes Review and improve existing core Agentic workflows Improve the quality of existing LLM outputs through prompting Introduce auto Value Proposition feature to production Review and reduce costs of existing pipelines by at-least 50% Why join Evergrowth Direct impact and ownership: report to More ❯

and ship agent workflows in Python Write excellent prompts and structured output schemas (JSON/JSON‐Schema, Pydantic) that are robust across models and providers. Integrate and operate multiple LLM providers (OpenAI primarily, also Anthropic and Google today, evaluate Groq/Cerebras and others for cost/latency/perf). Build observability for LLM calls: tracing, logging, cost accounting … to validate outputs with users, and iterate quickly. Our current/target stack (you don't need all of this) Python: 3.12+, FastAPI, Pydantic, asyncio/httpx, pytest, mypy LLM orchestration & evals: OpenAI/Anthropic/Gemini; Orq.ai and LangSmith are in use today (nice‐to‐have, not required); experience with lightweight, framework‐agnostic patterns is valued. Data & infra: SQL … RAG, Guardrails/Outlines/Instructor. Vector DBs, embeddings, and data pipelines. First 90 days - example outcomes Review and improve existing core Agentic workflows Improve the quality of existing LLM outputs through prompting Introduce auto Value Proposition feature to production Review and reduce costs of existing pipelines by at-least 50% Why join Evergrowth Direct impact and ownership: report to More ❯

integrate them into sites, videos and real‐world systems. We’re looking for an AI Infrastructure Engineer to build and scale the systems behind the AI video generation and LLM models. You’ll work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage … ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding More ❯

integrate them into sites, videos and real‐world systems. We’re looking for an AI Infrastructure Engineer to build and scale the systems behind the AI video generation and LLM models. You’ll work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage … ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding More ❯

integrate them into sites, videos and real‐world systems. We’re looking for an AI Infrastructure Engineer to build and scale the systems behind the AI video generation and LLM models. You’ll work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage … ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding More ❯

integrate them into sites, videos and real‐world systems. We’re looking for an AI Infrastructure Engineer to build and scale the systems behind the AI video generation and LLM models. You’ll work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage … ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding More ❯

integrate them into sites, videos and real‐world systems. We’re looking for an AI Infrastructure Engineer to build and scale the systems behind the AI video generation and LLM models. You’ll work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage … ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding More ❯

integrate them into sites, videos and real‐world systems. We’re looking for an AI Infrastructure Engineer to build and scale the systems behind the AI video generation and LLM models. You’ll work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage … ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding More ❯

integrate them into sites, videos and real‐world systems. We’re looking for an AI Infrastructure Engineer to build and scale the systems behind the AI video generation and LLM models. You’ll work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage … ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding More ❯

integrate them into sites, videos and real‐world systems. We’re looking for an AI Infrastructure Engineer to build and scale the systems behind the AI video generation and LLM models. You’ll work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage … ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding More ❯

integrate them into sites, videos and real‐world systems. We’re looking for an AI Infrastructure Engineer to build and scale the systems behind the AI video generation and LLM models. You’ll work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage … ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding More ❯

integrate them into sites, videos and real‐world systems. We’re looking for an AI Infrastructure Engineer to build and scale the systems behind the AI video generation and LLM models. You’ll work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage … ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding More ❯

integrate them into sites, videos and real‐world systems. We’re looking for an AI Infrastructure Engineer to build and scale the systems behind the AI video generation and LLM models. You’ll work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage … ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding More ❯

you will work on a variety of exciting projects, including consumer-focused features like the Energy Co-pilot and the Speedy Onboarding process (leveraging tools such as VLM/LLM). You will also collaborate across teams to build AI tools that enhance productivity and streamline processes within Fuse Energy. Design, develop, and deploy AI-powered features that directly impact … a focus on automation and enhancing workflows. Collaborate with backend engineers and data scientists to integrate AI-driven features into our platforms. Continuously improve and optimise AI models (including LLM and VLM) to provide a better user experience. Develop scalable, maintainable AI infrastructure to support a growing set of consumer-facing and internal AI features. Collaborate with the trading and … AI or machine learning. Strong programming skills in Python (or similar languages) with familiarity in AI/ML libraries (TensorFlow, PyTorch, etc.). Experience working with large-scale models (LLM/VLM) and deploying AI-driven solutions into production. Solid understanding of cloud technologies, containerization, and building scalable AI applications. Ability to integrate AI/ML models into real-world More ❯

Senior LLM Engineer – London | Hybrid (2 days per week on-site, Bank area) My client is a long-established consultancy that originally built its reputation in data engineering and wider data transformation, and over the past few years has grown a strong applied AI practice. They tend to work with UK organisations where data security, reliability and explainability actually matter … group is around eight senior engineers, with backing to grow sensibly (not a hiring spree). This role sits within that team and is focused on designing and deploying LLM systems that make it into production, are cost-efficient, and work reliably in the real world. What you’ll be doing: • Owning the design and build of LLM-based systems … and privacy are real constraints • Working closely with both internal engineers and client teams to ensure what gets built actually lands well What they’re looking for: • Hands-on LLM experience beyond prototyping/notebooks • Strong Python and experience with PyTorch/Hugging Face/similar tooling • Experience deploying models into production (not just training them) • Familiarity with vector stores More ❯

Senior LLM Engineer – London | Hybrid (2 days per week on-site, Bank area) My client is a long-established consultancy that originally built its reputation in data engineering and wider data transformation, and over the past few years has grown a strong applied AI practice. They tend to work with UK organisations where data security, reliability and explainability actually matter … group is around eight senior engineers, with backing to grow sensibly (not a hiring spree). This role sits within that team and is focused on designing and deploying LLM systems that make it into production, are cost-efficient, and work reliably in the real world. What you’ll be doing: • Owning the design and build of LLM-based systems … and privacy are real constraints • Working closely with both internal engineers and client teams to ensure what gets built actually lands well What they’re looking for: • Hands-on LLM experience beyond prototyping/notebooks • Strong Python and experience with PyTorch/Hugging Face/similar tooling • Experience deploying models into production (not just training them) • Familiarity with vector stores More ❯

Senior LLM Engineer – London | Hybrid (2 days per week on-site, Bank area) My client is a long-established consultancy that originally built its reputation in data engineering and wider data transformation, and over the past few years has grown a strong applied AI practice. They tend to work with UK organisations where data security, reliability and explainability actually matter … group is around eight senior engineers, with backing to grow sensibly (not a hiring spree). This role sits within that team and is focused on designing and deploying LLM systems that make it into production, are cost-efficient, and work reliably in the real world. What you’ll be doing: • Owning the design and build of LLM-based systems … and privacy are real constraints • Working closely with both internal engineers and client teams to ensure what gets built actually lands well What they’re looking for: • Hands-on LLM experience beyond prototyping/notebooks • Strong Python and experience with PyTorch/Hugging Face/similar tooling • Experience deploying models into production (not just training them) • Familiarity with vector stores More ❯

Senior LLM Engineer – London | Hybrid (2 days per week on-site, Bank area) My client is a long-established consultancy that originally built its reputation in data engineering and wider data transformation, and over the past few years has grown a strong applied AI practice. They tend to work with UK organisations where data security, reliability and explainability actually matter … group is around eight senior engineers, with backing to grow sensibly (not a hiring spree). This role sits within that team and is focused on designing and deploying LLM systems that make it into production, are cost-efficient, and work reliably in the real world. What you’ll be doing: • Owning the design and build of LLM-based systems … and privacy are real constraints • Working closely with both internal engineers and client teams to ensure what gets built actually lands well What they’re looking for: • Hands-on LLM experience beyond prototyping/notebooks • Strong Python and experience with PyTorch/Hugging Face/similar tooling • Experience deploying models into production (not just training them) • Familiarity with vector stores More ❯

Senior LLM Engineer – London | Hybrid (2 days per week on-site, Bank area) My client is a long-established consultancy that originally built its reputation in data engineering and wider data transformation, and over the past few years has grown a strong applied AI practice. They tend to work with UK organisations where data security, reliability and explainability actually matter … group is around eight senior engineers, with backing to grow sensibly (not a hiring spree). This role sits within that team and is focused on designing and deploying LLM systems that make it into production, are cost-efficient, and work reliably in the real world. What you’ll be doing: • Owning the design and build of LLM-based systems … and privacy are real constraints • Working closely with both internal engineers and client teams to ensure what gets built actually lands well What they’re looking for: • Hands-on LLM experience beyond prototyping/notebooks • Strong Python and experience with PyTorch/Hugging Face/similar tooling • Experience deploying models into production (not just training them) • Familiarity with vector stores More ❯

Job Title: AI Researcher Location: Cambridge or London, UK This is a permanent position with candidates required to do hybrid working in either Cambridge or London. Our client are looking for AI Researchers specialising in Reinforcement Learning with Human Feedback More ❯

Job Title: AI Researcher Location: Cambridge or London, UK This is a permanent position with candidates required to do hybrid working in either Cambridge or London. Our client are looking for AI Researchers specialising in Reinforcement Learning with Human Feedback More ❯