1,051 to 1,075 of 1,566 LLM Jobs in England

Applied AI Software Engineer - Python, Fast API, AWS, LLMs OB are partnered with a high-growth, B2B SaaS start-up who are looking to hire a highly skilled Applied AI Engineer to their Product Engineering team, where you'll pioneer More ❯

Version Control: Git/GitHub System Integration & Deployment Model Deployment: Flask, FastAPI, MLflow Model Serving: Triton Inference Server, Hugging Face Inference Endpoints API Integration: OpenAI, Anthropic, Cohere, Mistral APIs LLM Frameworks: LangChain, LlamaIndex – for building LLM-powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise data More ❯

Version Control: Git/GitHub System Integration & Deployment Model Deployment: Flask, FastAPI, MLflow Model Serving: Triton Inference Server, Hugging Face Inference Endpoints API Integration: OpenAI, Anthropic, Cohere, Mistral APIs LLM Frameworks: LangChain, LlamaIndex – for building LLM-powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise data More ❯

Version Control: Git/GitHub System Integration & Deployment Model Deployment: Flask, FastAPI, MLflow Model Serving: Triton Inference Server, Hugging Face Inference Endpoints API Integration: OpenAI, Anthropic, Cohere, Mistral APIs LLM Frameworks: LangChain, LlamaIndex – for building LLM-powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise data More ❯

Version Control: Git/GitHub System Integration & Deployment Model Deployment: Flask, FastAPI, MLflow Model Serving: Triton Inference Server, Hugging Face Inference Endpoints API Integration: OpenAI, Anthropic, Cohere, Mistral APIs LLM Frameworks: LangChain, LlamaIndex – for building LLM-powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise data More ❯

Version Control: Git/GitHub System Integration & Deployment Model Deployment: Flask, FastAPI, MLflow Model Serving: Triton Inference Server, Hugging Face Inference Endpoints API Integration: OpenAI, Anthropic, Cohere, Mistral APIs LLM Frameworks: LangChain, LlamaIndex – for building LLM-powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise data More ❯

by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly. As an Applied AI ML Director - NLP/LLM and Graphs within the Chief Data & Analytics Office, Machine Learning Centre of Excellence, you will have the opportunity to apply sophisticated machine learning methods to complex tasks including natural language … Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science Or an MS with significant years of industry or research experience in the field. Solid background in NLP, LLM and graph analytics and hands-on experience and solid understanding of machine learning and deep learning methods Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy More ❯

robust, reliable, and user-focused AI services across our business. What You’ll Do Design and implement a comprehensive AI testing and evaluation framework for all AI solutions, including LLM-based tools, RAG systems, and third-party platforms. Define and document quality standards for semantic accuracy, factual consistency, bias, tone, and relevance. Develop reusable testing templates, data sets, and evaluation … practices to ensure fairness, transparency, and user trust. What You’ll Bring Strong hands-on experience in testing and evaluation of AI or software systems, ideally with NLP or LLM-based applications. Understanding of prompt evaluation, semantic search, and LLM behaviour (accuracy, hallucination, bias, tone, etc.). Familiarity with tools like Trulens, HumanLoop, PromptLayer, or similar; experience designing QA approaches More ❯

robust, reliable, and user-focused AI services across our business. What You’ll Do Design and implement a comprehensive AI testing and evaluation framework for all AI solutions, including LLM-based tools, RAG systems, and third-party platforms. Define and document quality standards for semantic accuracy, factual consistency, bias, tone, and relevance. Develop reusable testing templates, data sets, and evaluation … practices to ensure fairness, transparency, and user trust. What You’ll Bring Strong hands-on experience in testing and evaluation of AI or software systems, ideally with NLP or LLM-based applications. Understanding of prompt evaluation, semantic search, and LLM behaviour (accuracy, hallucination, bias, tone, etc.). Familiarity with tools like Trulens, HumanLoop, PromptLayer, or similar; experience designing QA approaches More ❯

robust, reliable, and user-focused AI services across our business. What You’ll Do Design and implement a comprehensive AI testing and evaluation framework for all AI solutions, including LLM-based tools, RAG systems, and third-party platforms. Define and document quality standards for semantic accuracy, factual consistency, bias, tone, and relevance. Develop reusable testing templates, data sets, and evaluation … practices to ensure fairness, transparency, and user trust. What You’ll Bring Strong hands-on experience in testing and evaluation of AI or software systems, ideally with NLP or LLM-based applications. Understanding of prompt evaluation, semantic search, and LLM behaviour (accuracy, hallucination, bias, tone, etc.). Familiarity with tools like Trulens, HumanLoop, PromptLayer, or similar; experience designing QA approaches More ❯

robust, reliable, and user-focused AI services across our business. What You’ll Do Design and implement a comprehensive AI testing and evaluation framework for all AI solutions, including LLM-based tools, RAG systems, and third-party platforms. Define and document quality standards for semantic accuracy, factual consistency, bias, tone, and relevance. Develop reusable testing templates, data sets, and evaluation … practices to ensure fairness, transparency, and user trust. What You’ll Bring Strong hands-on experience in testing and evaluation of AI or software systems, ideally with NLP or LLM-based applications. Understanding of prompt evaluation, semantic search, and LLM behaviour (accuracy, hallucination, bias, tone, etc.). Familiarity with tools like Trulens, HumanLoop, PromptLayer, or similar; experience designing QA approaches More ❯

robust, reliable, and user-focused AI services across our business. What You’ll Do Design and implement a comprehensive AI testing and evaluation framework for all AI solutions, including LLM-based tools, RAG systems, and third-party platforms. Define and document quality standards for semantic accuracy, factual consistency, bias, tone, and relevance. Develop reusable testing templates, data sets, and evaluation … practices to ensure fairness, transparency, and user trust. What You’ll Bring Strong hands-on experience in testing and evaluation of AI or software systems, ideally with NLP or LLM-based applications. Understanding of prompt evaluation, semantic search, and LLM behaviour (accuracy, hallucination, bias, tone, etc.). Familiarity with tools like Trulens, HumanLoop, PromptLayer, or similar; experience designing QA approaches More ❯

robust, reliable, and user-focused AI services across our business. What You'll Do Design and implement a comprehensive AI testing and evaluation framework for all AI solutions, including LLM-based tools, RAG systems, and third-party platforms. Define and document quality standards for semantic accuracy, factual consistency, bias, tone, and relevance. Develop reusable testing templates, data sets, and evaluation … practices to ensure fairness, transparency, and user trust. What You'll Bring Strong hands-on experience in testing and evaluation of AI or software systems, ideally with NLP or LLM-based applications. Understanding of prompt evaluation, semantic search, and LLM behaviour (accuracy, hallucination, bias, tone, etc.). Familiarity with tools like Trulens, HumanLoop, PromptLayer, or similar; experience designing QA approaches More ❯

of applied research, platform integration, and engineering-minded data science. What You’ll Be Doing Build and deploy a wide variety of models spanning classification, regression, propensity scoring, and LLM-based use cases Spearhead the entire company’s GenAI efforts. The team have multiple LLM projects running but would love a technical leader in this area Own the end-to … to both traditional ML and generative AI Strong belief in data science as a product, not just a modelling function Clear evidence of commercially successful/or centrally impactful LLM based work for previous companies. Proven track record deploying real-time models into production environments Technical depth in Python, software engineering principles, and deployment tooling Familiarity with experimentation frameworks and More ❯

of applied research, platform integration, and engineering-minded data science. What You’ll Be Doing Build and deploy a wide variety of models spanning classification, regression, propensity scoring, and LLM-based use cases Spearhead the entire company’s GenAI efforts. The team have multiple LLM projects running but would love a technical leader in this area Own the end-to … to both traditional ML and generative AI Strong belief in data science as a product, not just a modelling function Clear evidence of commercially successful/or centrally impactful LLM based work for previous companies. Proven track record deploying real-time models into production environments Technical depth in Python, software engineering principles, and deployment tooling Familiarity with experimentation frameworks and More ❯

of applied research, platform integration, and engineering-minded data science. What You’ll Be Doing Build and deploy a wide variety of models spanning classification, regression, propensity scoring, and LLM-based use cases Spearhead the entire company’s GenAI efforts. The team have multiple LLM projects running but would love a technical leader in this area Own the end-to … to both traditional ML and generative AI Strong belief in data science as a product, not just a modelling function Clear evidence of commercially successful/or centrally impactful LLM based work for previous companies. Proven track record deploying real-time models into production environments Technical depth in Python, software engineering principles, and deployment tooling Familiarity with experimentation frameworks and More ❯

of applied research, platform integration, and engineering-minded data science. What You’ll Be Doing Build and deploy a wide variety of models spanning classification, regression, propensity scoring, and LLM-based use cases Spearhead the entire company’s GenAI efforts. The team have multiple LLM projects running but would love a technical leader in this area Own the end-to … to both traditional ML and generative AI Strong belief in data science as a product, not just a modelling function Clear evidence of commercially successful/or centrally impactful LLM based work for previous companies. Proven track record deploying real-time models into production environments Technical depth in Python, software engineering principles, and deployment tooling Familiarity with experimentation frameworks and More ❯

of applied research, platform integration, and engineering-minded data science. What You’ll Be Doing Build and deploy a wide variety of models spanning classification, regression, propensity scoring, and LLM-based use cases Spearhead the entire company’s GenAI efforts. The team have multiple LLM projects running but would love a technical leader in this area Own the end-to … to both traditional ML and generative AI Strong belief in data science as a product, not just a modelling function Clear evidence of commercially successful/or centrally impactful LLM based work for previous companies. Proven track record deploying real-time models into production environments Technical depth in Python, software engineering principles, and deployment tooling Familiarity with experimentation frameworks and More ❯

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 interest Here at Burns Sheehan, we’re working with a leading UK tech business in the payments and financial services space - processing billions in transactions … 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 ❯

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 interest Here at Burns Sheehan, we’re working with a leading UK tech business in the payments and financial services space - processing billions in transactions … 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 ❯

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 interest Here at Burns Sheehan, we’re working with a leading UK tech business in the payments and financial services space - processing billions in transactions … 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 ❯

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 interest Here at Burns Sheehan, we’re working with a leading UK tech business in the payments and financial services space - processing billions in transactions … 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 ❯

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 interest Here at Burns Sheehan, we’re working with a leading UK tech business in the payments and financial services space - processing billions in transactions … 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 ❯

Senior Software/Platform Engineer (LLM/AI Interest) Brand new AI Platform London - 4 days a week in office (Paddington) Python, GCP, Kubernetes, Terraform, CI/CD, AI/LLM interest Here at Burns Sheehan, were working with a leading UK tech business in the payments and financial services space - processing billions in transactions each year and supporting around … and product teams to deliver safe, production-ready AI systems. Strong background in Software or Platform Engineering - ideally with Python, Java or Go. Interest or experience in AI infrastructure, LLM tooling, or AI platform enablement. If youre interested in helping build real AI infrastructure within a fast-moving, product-led business thats making a visible impact across the UK - get … in touch to find out more. Senior Software/Platform Engineer (LLM/AI Interest) Brand new AI Platform More ❯

to work at the cutting edge of generative AI — turning research into production-ready systems that make a real business impact. What you’ll be doing Designing and deploying LLM-powered agents end-to-end — from research to production. Developing tools, frameworks, and annotation workflows to refine agent behaviour. Defining what “ production-quality code ” means for LLMs and teaching agents … we’re looking for 2+ years’ hands-on experience in ML/AI (recommendation systems, data mining, or similar). Proven track record of building or deploying GenAI/LLM systems into production. Strong Python skills, with experience in PyTorch or TensorFlow . Understanding of MLOps practices (evaluation, monitoring, scaling). Master’s (or equivalent experience) in Computer Science, AI … ML, or related field. ⭐ Bonus points for: experience designing annotation schemas, Kaggle Master credentials, or published research. 📩 Ready to help shape the future of LLM agents? Apply now and join us at the frontline of AI innovation . Send CV to kacey.norris@experis.co.uk for immediate consideration. More ❯