51 to 75 of 980 LLM Jobs in the UK

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 ...

field engineering, or solution consulting. Proven ability to lead initiatives from conception to delivery over at least 3+ years. Technical Mastery: Strong grasp of LLM‐based systems and GenAI pipelines including prompt engineering, retrieval‐augmented generation (RAG), orchestration, and data modeling. Experience designing full‐stack intelligent workflows. Cloud & Infrastructure Fluency ...

systems. Familiarity with frameworks such as OWASP Top 10 for LLMs and NIST AI Risk Management Framework. Experience securing advanced AI patterns such as LLM integrations, APIs, MCPs, RAG pipelines, or model services (preferred). Experience leading implementation and adoption of CNAPP platforms. Deep understanding of cloud detection and response ...

documented code. Experience developing and deploying machine learning, AI or data‐driven systems in production or near‐production settings. Experience with generative AI systems, LLM‐enabled applications or evaluation pipelines. Experience with cloud platforms, MLOps tooling, model serving or platform engineering. Advanced use of Linux, Docker, version control, CI/ ...

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

graph and keyword search, with reranking and embedding‐model selection), knowledge bases, knowledge graphs and ontologies, agentic workflows and skills, evaluation methods (eval harnesses, LLM‐as‐judge, groundedness and faithfulness metrics, tracing), and model risk controls. Experience building secure, scalable and reliable AI solutions in enterprise environments, including governance, permissions ...

helped design Excellent communication skills Eligible for SC clearance Nice to have Practical MLOps experience in live environments Kubernetes and IaC Experience with LLM or agent‐based systems Open source contributions or technical writing Perks £65k–£80k salary EMI share scheme Personal L&D budget 25 days holiday (rising ...

maintaining modern applications across front-end and back-end, leveraging AWS for scalability and security, while incorporating AI/ML capabilities such as LLM-powered features, intelligent APIs, and automation workflows. Qualifications Front-End Development Build responsive, accessible UI using HTML5, CSS3, TypeScript, and React. Optimize performance and implement unit ...

human in the loop. Advanced modern JavaScript/TypeScript, NodeJS and React. Web development principles (REST, SPA...). Microservice architecture, AWS and DevOps. Building LLM-powered features: tool-calling, retrieval-augmented generation (RAG), evaluation/eval harnesses and observability (desirable). Familiarity with model-agnostic tooling and routing, e.g. ...

modern MLOps practices. Commitment to people development: mentoring, performance conversations, and building high‐performing teams. Bonus: experience with NLP on financial contracts, RAG or LLM‐based applications on structured data, large‐scale loan data pipelines, or containerization tooling (Docker, Kubernetes, Terraform). Competitive salary and performance‐based bonus. Stock option ...

python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch). Experience working with language models like LLM APIs and optimizing their usage for specific applications. Experience with programming languages: Python, C++, Java, R, SQL. Strong written & verbal communication skills and ability to communicate ...

large, multi‐team deliveries – setting strategy, making architectural decisions and enabling teams to deliver at pace. Hands‐on experience with agentic AI: building LLM‐powered applications/agents, tool use, orchestration, retrieval (RAG), prompt and safety engineering, evaluation and telemetry. Proficient knowledge of cloud‐native engineering: containers (GKE/Cloud ...

designing and delivering agentic AI solutions that integrate with enterprise data, APIs, workflows, business systems and human‐in‐the‐loop processes Strong understanding of LLM capabilities and limitations, including prompt design, retrieval‐augmented generation, hallucination management, tool use, evaluation and monitoring Experience with AI governance and responsible AI, including agent ...

large‐scale consumer applications Previous experience as a site lead, office lead, or similar multi‐team leadership role Background in building infrastructure for LLM training or inference Contributions to open‐source infrastructure or AI infrastructure projects Experience scaling teams from 0 to 20+ engineers Active involvement in the London ...

stakeholders Your Skills Software engineering experience while leading engineering teams Strong hands‐on experience building and deploying AI applications in production Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns Experience with agentic frameworks and autonomous agent architectures Proficiency in Python and modern software development practices (testing, code ...

breakthroughs into practical solutions for various nation states, making AI technology both accessible and influential. In This Role, You Will: Design and deploy advanced LLM models to tackle real‐world problems, especially automating complex, manual processes in a range of verticals. Build scalable data pipelines, optimize models for performance ...

make a significant impact by making AI technology both accessible and influential. In This Role, You Will: Innovate and Deploy: Design and deploy advanced LLM models to tackle real‐world problems, particularly in automating complex, manual processes in a range of real‐world verticals. Optimize and Scale: Build scalable data ...

developer platforms, internal tooling, shared services, or infrastructure that supports multiple engineering teams. Hands-on experience building AI-powered applications and services using modern LLM frameworks and agentic architectures. Good understanding of modern AI concepts and practices, including: Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Prompt Engineering AI Guardrails ...

Azure, leveraging core technologies in the AI Foundry ecosystem, understanding different business challenges require varied solutions from SLM's to intelligent Agentic automation from LLM foundational models, Human in the Loop and MLOps. Data Architecture Design: You understand and know when to use the following data architecture design patterns ...

Databricks, Azure DevOps, GitHub, Kubernetes, containerisation or equivalent enterprise DevOps platforms. Experience supporting AI, machine learning, data science, analytics or automation teams. Experience with LLM application architecture, RAG, vector stores, orchestration frameworks, model APIs or context management. Experience integrating third‐party or public data APIs into enterprise environments. Experience defining ...

audit standards Champion scalable, secure, and efficient AI implementation. What We're Looking For Core Skills & Experience Strong experience in AI Engineering, ML/LLM applications, or intelligent automation Solid Java engineering background with production-quality coding practices Experience with CI/CD tools e.g., Jenkins, GitLab CI Hands ...

Enhanced Engineering: Agentic and AI-assisted development as a daily practice (Claude, GitHub Copilot and similar), plus awareness of AI/ML and LLM integration. We give every engineer Claude and ChatGPT seats and expect them to be used hard and used well. Collaboration & Communication Work closely with Product Managers ...

techniques, and algorithms with the right architecture, and begin to guide junior engineers on the project. You stay current with knowledge engineering, generative AI, LLM, and multi-modal models; look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help ...

love to see: Bloomberg Terminal, BQL, Enterprise, or Bloomberg data workflow experience. Experience productionizing AI, machine learning, anomaly detection, NLP, classification, or LLM‐assisted workflows. Experience with cloud platforms, CI/CD, automated testing, version control, metadata management, lineage, or modern DataOps practices. Project management experience with Agile delivery, backlog ...