1 to 25 of 981 LLM Jobs in the UK

agent behaviours, defining secure, scalable solution architectures. Build and maintain AI components (e.g. RAG, classification, recommendation, summarisation) using Python and modern ML/LLM frameworks. Implement end-to-end MLOps pipelines for development, testing, deployment and monitoring of Copilot and AI solutions, and deploy them into production environments (e.g. Microsoft ...

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 ...

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. ...

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. ...

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 ...

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 ...

Augmented Generation applications, AI agents and 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) and 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. ...

Augmented Generation applications, AI agents and 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) and transforming it into usable structured formats.* Experience building chatbots, search systems, or generative ...

Design, build, and deploy AI‐powered applications (chatbots, copilots, document intelligence, decision‐support tools) for insurance use cases; implement Retrieval‐Augmented Generation patterns; build LLM‐based workflows and agents. Cloud & Platform Engineering (GCP): Deploy solutions on GCP leveraging Vertex AI, BigQuery, Cloud Run, secure API integrations; build scalable, resilient, compliant ...

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 ...

Preferred qualifications, capabilities, and skills Experience with data, AWS and AIML engineering in commercial settings, preferably in financial sector Experience working on recommendation systems, LLM applications or other AI/ML systems Practical experience with Kubernetes, EKS, Docker, MLOps Prior exposure to LLMs, RAG, Knowledge Graph Technologies, OpenSearch and vector ...

Snowflake . Experience with CI/CD and version control tools (Git, TeamCity or similar). Understanding of AI governance, prompt engineering, and LLM frameworks. Desirable Experience supporting business-critical financial applications. Knowledge of trading, securities, or capital markets. What We're Looking For Excellent communication and stakeholder management skills. ...

Senior AI Engineer/AI Engineering Consultant/Generative AI Consultant/Senior Machine Learning Engineer/AI & ML Consultant/MLOps Engineer/LLM Engineer/AI Engineering Consultant/Senior AI Engineer/Generative AI Engineer/AI Solutions Architect/Data & AI Consultant/AI Solutions Consultant ...

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 ...

engagements using modern full stack technologies. Integrate Azure AI services (Azure OpenAI, Cognitive Services, Azure ML, AI Search) into production applications. Architect and build LLM-powered features, agentic workflows, and MCP (Model Context Protocol) integrations to a production standard. Work directly with clients to understand requirements, shape solutions, and translate ...

platforms. Demonstrates experience of cloud platforms such as Azure and AWS, with experience supporting and maintaining cloud-based infrastructure. Hands-on experience working with: LLM-based solutions, including Retrieval-Augmented Generation techniques and prompt engineering approaches Data processing frameworks and platforms, including batch and streaming pipelines Practical understanding of MLOps ...

framework (PyTorch, TensorFlow, JAX) Solid grounding in core ML—supervised, unsupervised, evaluation, regularisation, statistics Production ML experience—deploying, serving and monitoring models at scale LLM and generative AI tooling exposure (LangChain, LlamaIndex, vector databases such as Pinecone, Weaviate or pgvector, RAG patterns, fine-tuning workflows) MLOps platforms (MLflow, Kubeflow, Vertex ...

make myself available outside of normal working hours to suit your schedule. KEY SKILLS AI Software Engineer/Machine Learning Engineer/LLM Engineer/Python/AWS/Azure/Docker/Kubernetes/Generative AI/NLP/RAG/MLOps/UKSV DV/Outside IR35/ ...

make myself available outside of normal working hours to suit your schedule. KEY SKILLS AI Software Engineer/Machine Learning Engineer/LLM Engineer/Python/AWS/Azure/Docker/Kubernetes/Generative AI/NLP/RAG/MLOps/UKSV DV/Outside IR35/ ...

APIs, tooling, and bespoke logic. Architecture & Standards: Architect robust, scalable, and compliant Agentic AI solutions across industries. Lead multi‐agent orchestration, RAG pipelines, and LLM/SLM integration design. Champion observability, telemetry, and auditable AI standards. Build and maintain reusable frameworks and asset libraries. Team & Product: Help build and guide ...