1 to 25 of 1,595 LLM Jobs in England

understanding of the distinction between Generative AI and Agentic AI, including their foundations, capabilities, and appropriate use cases. Strong understanding of AI, ML and LLM concepts, including prompt engineering, prompt grounding, iterative loop techniques, context windows, embeddings, RAG, agentic workflows. Proven ability to integrate AI capabilities both into low-code ...

date on market trends, new opportunities, and the changing landscape of AI technologies. Experience AI Orchestration & Development: Expert‐level experience building complex LLM‐powered systems and multi‐agent workflows using frameworks like LangGraph, LangChain, AutoGen, or ADK. Artificial Intelligence & Machine Learning: Deep practical understanding of machine learning algorithms, natural language ...

technical stakeholders and to articulate a clear technical vision that aligns with business goals. Technical Skills AI/GenAI/Agentic Platforms LLM & Agentic Frameworks: Deep expertise in building production‐grade agentic systems using GCP as primary (ADK, Vertex AI) Multi‐Agent Systems: Hands‐on experience designing and implementing multi ...

environments Design and build scalable backend platforms, APIs, and services that power AI applications, intelligent automation solutions, and AI agents Develop and deploy advanced LLM-powered applications using techniques such as retrieval-augmented generation, prompt engineering, evaluation frameworks, and model optimization Create robust data and inference pipelines that support both ...

trends in machine learning, AI, and cloud technologies (particularly Azure) Support the development of data science best practices and standards across the organisation AI & LLM Applications Intelligent triage support tools for customer interactions Knowledge retrieval systems for operational teams Automated insight generation and decision support What you’ll need Hands ...

trends in machine learning, AI, and cloud technologies (particularly Azure) Support the development of data science best practices and standards across the organisation AI & LLM Applications Intelligent triage support tools for customer interactions Knowledge retrieval systems for operational teams Automated insight generation and decision support What you’ll need Hands ...

tools for insurance use cases.* Implement Retrieval‐Augmented Generation (RAG) patterns using structured and unstructured insurance data (policies, submissions, bordereaux, claims documents).* Build LLM‐based workflows and agents using platforms such as ChatGPT (OpenAI) and Claude (Anthropic).**Cloud & Platform Engineering (GCP)*** Develop and deploy AI solutions on Google ...

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 ...

technical stakeholders and to articulate a clear technical vision that aligns with business goals. Technical Skills AI/GenAI/Agentic Platforms LLM & Agentic Frameworks: Deep expertise in building production‐grade agentic systems using GCP as primary (ADK, Vertex AI) Multi‐Agent Systems: Hands‐on experience designing and implementing multi ...

field, or demonstrable relevant experience. Additional desired skills Knowledge of vector databases and retrieval strategies. Experience with recommender systems and ranking models. Familiarity with LLM evaluation tools (e.g., RAGAS, TruLens, LangSmith, Arize). A working understanding of cloud networking and platform infrastructure. Experience in e‐commerce or retail environments. ...

above, we would LOVE if you have Knowledge of vector databases and retrieval strategies. Experience with recommender systems and ranking models. Familiarity with LLM evaluation tools (e.g., RAGAS, TruLens, LangSmith, Arize). A working understanding of cloud networking and platform infrastructure. Experience in e-commerce or retail environments. Why join ...

Retrieval Augmented Generation applications, AI agents & systems built around them. Experience using GenAI frameworks such as LlamaIndex, Crew AI, AutoGen, or similar agentic/LLM orchestration toolkits. Exposure to working with unstructured data (documents, conversations, images) & transforming it into usable structured formats. Experience building chatbots, search systems, or generative ...

such as PyTorch, TensorFlow, and Hugging Face. Experience taking AI proof-of-concepts from idea to production. Strong knowledge of deep learning, NLP, and LLM architectures and experience in fine-tuning LLMs or training domain-specific models, RAG, embeddings, and vector databases. Familiarity with agentic AI concepts and orchestration frameworks. ...

equivalent in Statistics,Mathematics, Econometrics or similar discipline with at least 8-12 years’experience on data science/AI projects. Deep understanding of LLM families (GPT, Llama,Claude, Mistral) and their reasoning capabilities. S trong experience with Databricks- DLT,Delta Lake concepts, UC governance. Solid understanding of streamingtechnologies (e.g. ...

technical challenges unique to your sector and have delivered AI solutions within it. Typical projects include: Building AI agents and autonomous workflows Developing LLM-powered applications and copilots Designing enterprise RAG and knowledge retrieval platforms Production deployment of Generative AI solutions AI integration into enterprise products and business platforms Scaling ...

essential: - Strong general-purpose programming (most commonly Python) applied to AI/ML systems - Semantic search, vector/embedding infrastructure, and RAG pipeline construction - LLM orchestration and agentic frameworks (eg LangChain/LlamaIndex-style tooling, multi-agent patterns) - Prompt engineering and systematic evaluation/guardrail tooling (hallucination detection, safety testing ...

application programming interfaces, data pipelines, inference pipelines, and platform capabilities that support real‐time and batch AI workloads at enterprise scale Implement advanced large language model applications using retrieval‐augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration Make key technical decisions while remaining accountable ...

encompassing:Compute & Services: Java, .NET, Python, Cloud-native microservicesData & Analytics: Databricks, Microsoft Fabric, AWS Glue, Athena, Event Streaming (e.g., Kafka)AI & ML: Azure OpenAI, LLM Integration patterns, Vector DatabasesIntegration & Storage: Azure Data Factory (ADF), SQL Server, Enterprise relational platformsInfrastructure: Azure, AWS, and Hybrid Cloud networksCandidates are not expected ...

testing frameworks, monitoring, and quality controls in production environments.LLMs and generative AI — practical understanding of how to engineer data products and pipelines that support LLM and GenAI use cases.Technical leadership — track record of engineering and architectural decision-making, setting engineering standards and delivering high quality, innovative and automated ...

infrastructure-as-code tools, and containerization/orchestration tools (Docker, Kubernetes) to operate, support, and secure mission-critical applications Previous experience deploying and managing LLM-model based applications and agents Exposure to vector stores such as Pinecone, GCP RAG engine, and AWS S3 Vector Buckets Exposure to cloud-native microservices ...

infrastructure-as-code tools, and containerization/orchestration tools (Docker, Kubernetes) to operate, support, and secure mission-critical applications Previous experience deploying and managing LLM-model based applications and agents Exposure to vector stores such as Pinecone, GCP RAG engine, and AWS S3 Vector Buckets Exposure to cloud-native microservices ...

configuration, or a related role.Strong practical experience using generative AI tools to improve analysis, documentation, coding, research, workflow automation, or business productivity.Working knowledge of LLM concepts, including prompting, context windows, retrieval, hallucination risk, structured outputs, model selection, and evaluation tradeoffs.Familiarity with applied AI patterns such as RAG, embeddings, vector search ...

engineering, data engineering, ML engineering, solution engineering, technical consulting, or related hands-on technical roles.2+ years of experience building or deploying AI, ML, GenAI, LLM, RAG, agentic AI, data science, or automation solutions.Hands-on experience with programming languages and frameworks such as Python, JavaScript/TypeScript, FastAPI, Flask, React, LangChain ...

applied experience Experienced in cloud development (AWS), with a focus on application design and development. Experience with AI/ML model integration, Prompt engineering, LLM APIs (OpenAI, Bedrock) and Generative AI Advanced in Java and Python Strong experience with cloud platforms like AWS, Azure, or Google Cloud Platform. Experience building ...

Generative AI use cases. Design and build APIs and microservices that integrate AI capabilities into internal and external workflows. Develop, fine‐tune, and deploy LLM‐based applications (e.g., chatbots, assistants, knowledge extraction tools). Architect scalable AI infrastructure on cloud platforms (AWS, GCP, or Azure), leveraging containerisation and IaC. Implement ...