1 to 25 of 598 LLM Jobs in England

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 ...

enhancement. The Role * Design and develop production-grade AI applications using both traditional Machine Learning and Generative AI approaches* Build and deploy RAG systems, LLM-powered applications and agentic workflows* Develop scalable APIs, microservices and cloud-native AI solutions* Work closely with business stakeholders to translate requirements into technical solutions ...

platforms for downstream data consumption, operational analytics and decision support. Experience architecting AI/ML and agentic automation solutions within trading technology estates, including LLM integration, RAG patterns, intelligent scheduling and predictive analytics. Familiarity with Agile/SAFe delivery frameworks at scale, with experience embedding architecture governance into sprint-based ...

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 ...

Python development skills and deep experience with modern AI/ML frameworks and SDKs. Proven experience designing and deploying production-grade RAG solutions and LLM-powered applications. Strong experience building and deploying AI agents, orchestration frameworks, and automated workflows. Experience with Azure AI Services, Azure OpenAI, Azure Machine Learning ...

Expertise: Proven experience developing and deploying intelligent conversational AI systems using RAG architectures, Model Context Protocol (MCP), AI-enabled search, vector databases, and LLM integration. Frameworks: Hands-on experience building GenAI applications using LangChain and LangGraph (agent architecture design, state management, and graph-based workflow orchestration). ML & Cloud Ecosystems ...

strategic concepts to diverse audiences, from engineers to executive leadership. Extensive experience designing, optimizing, and implementing strategic approaches to Model Context Protocols (MCP) for LLM-powered agents across multiple products, including advanced strategies for prompt engineering, context management, and memory architectures. Hands-on software engineering or data science experience, particularly ...

data infrastructure, and experience working within Financial Services or another regulated industry is essential. Technical skills relevant to this role include Python and SQL, LLM development techniques such as prompt engineering, fine-tuning and RAG, frameworks including LangChain and LangGraph, agent frameworks, vector databases, FastAPI, and cloud platforms such ...

data infrastructure, and experience working within Financial Services or another regulated industry is essential. Technical skills relevant to this role include Python and SQL, LLM development techniques such as prompt engineering, fine-tuning and RAG, frameworks including LangChain and LangGraph, agent frameworks, vector databases, FastAPI, and cloud platforms such ...

Nano/Pro/1.5) for multimodal reasoning; integrate via Vertex AI; grounding, structured output, function‐calling. Azure OpenAI/GPT‐4.x for enterprise LLM services; model selection, limits, rate management, content filters/AI safety. Amazon Q for developer and ops assistance across AWS stacks. Cursor, GitHub Copilot, Devin ...

deployment approaches Drive high-quality engineering practices across testing, deployment, monitoring, and optimisation Tech environment Key technologies include: Python Azure Databricks Generative AI/LLM frameworks Agentic AI tooling and orchestration frameworks LangChain/LangGraph PyTorch and ML libraries REST APIs Docker and containerisation CI/CD pipelines Git-based ...

engineering workflows Ability to critically evaluate, test, and improve AI-generated code and technical solutions Preferred Qualifications Experience building AI-powered applications or integrating LLM APIs Familiarity with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and AI agent architectures Experience integrating services from OpenAI, Anthropic, Google Gemini, or similar ...

AI Engineer Location: London (Hybrid - 2-3 days per week onsite) Salary: £80,000 - £120,000 + Benefits Type: Permanent About 167 Solutions 167 Solutions is a specialist technology recruitment consultancy connecting organisations with exceptional ...

AI Engineer Location: London (Hybrid - 2-3 days per week onsite) Salary: £80,000 - £120,000 + Benefits Type: Permanent About 167 Solutions 167 Solutions is a specialist technology recruitment consultancy connecting organisations with exceptional ...

maintain analytical models using Python, SQL and cloud-based data platforms • Apply machine learning, AI and statistical techniques to business challenges • Work with NLP, LLM and Generative AI technologies where appropriate • Validate data, perform testing and ensure analytical output quality • Monitor model performance and support ongoing optimisation and governance • Contribute ...

engineering domains. End-to-end exposure in model lifecycle development, including extensive experience training and deploying ML models in production environments. Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns. Experience in fine-tuning LLMs for domain-specific enterprise applications. Strong expertise in MLOps and LLMOps, ensuring scalable ...

Strong communication skills and the ability to work effectively across engineering, product and data teams Nice-to-haves Experience supporting computer vision, deep learning, LLM or other compute-intensive ML workloads Experience with GPU infrastructure, distributed training or high-performance compute environments Familiarity with feature stores, model registries and automated ...

articulate complex technical and strategic concepts to diverse audiences. Extensive experience designing, optimising, and implementing strategic approaches to Model Context Protocols (MCP) for LLM‐powered agents across multiple products. Hands‐on software engineering or data science experience, particularly in GenAI, prior to transitioning into product leadership. Proven ability to build ...

infrastructure engineering role - not a data science or ML engineering position. You'll own the runtime, infrastructure, and operational layers that RAG pipelines, LLM orchestration, vector search, and evaluation workflows run on, across AWS and Databricks. The focus is on building scalable, observable, secure, and cost-efficient platform infrastructure that ...

CloudWatch), GCP (BigQuery). Knowledge of Airflow, Kafka, Flink, dbt, Kubernetes is highly beneficial. Good understanding of AI platforms, experience building infrastructure for LLM orchestration (e.g., vector databases, RAG pipelines, GPU scaling) is a significant plus. #J-18808-Ljbffr ...

production deployment governance, and incident/root-cause management. Identify and deliver pragmatic AI/ML opportunities where valuable (e.g., agentic workflows, RAG/LLM-enabled capabilities) with appropriate governance and human-in-the-loop controls. What you need to have: Experience managing a team, as this role involves leading ...

adopt emerging AI and agent technologies. Hands-on experience with vector databases, embeddings, or prompt engineering. Understanding of AI fundamentals and experience using LLM APIs or AI-enhanced features and Agents. Experience with cloud services such as AWS, Azure, or serverless platforms. Interest in distributed systems, event-driven architectures ...

developments. Take on related responsibilities as the squad's needs evolve. Requirements: Engineering experience: 3+ years in software engineering, with hands-on experience building LLM-powered applications in production (RAG, tool-augmented agents or agentic workflows). Education: BS in Engineering, Computer Science, or equivalent. Ways of working: Comfortable working ...

implement AI/ML solutions for complex business problems and use cases Define reference architectures suitable to answer complex questions, including via code interpreting, LLM tool use and leveraging secondary data science models Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to internal ...

implement AI/ML solutions for complex business problems and use cases Define reference architectures suitable to answer complex questions, including via code interpreting, LLM tool use and leveraging secondary data science models Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to internal ...