Top AI Engineer Jobs in London

Build and ship agentic LLM systems for Treasury: cash monitoring, funding execution, narrative generation, and discovery-to-deployment pipelines. Create reusable agent infrastructure, governance, evaluation, and partner with engineering to ensure data accuracy while embedding with operators to scope and iterate solutions.

As a Forward Deployed AI Engineer, you'll design and deploy AI solutions for enterprise customers, integrating with their systems and ensuring successful adoption. You'll lead custom AI projects from prototyping to deployment, collaborating with various teams to meet customer needs.

The AI Engineer will focus on the lifecycle of production-grade AI, managing model training, fine-tuning, inference optimization, and production engineering, while collaborating with stakeholders to implement business requirements.

As an AI Engineer, you will architect, develop, and deploy scalable AI applications, collaborating with teams to implement AI solutions that drive enterprise productivity and innovation.

Design, build, and deploy production-ready AI algorithms and high-scale evaluation pipelines focused on LLMs and patent generation. Implement advanced prompt engineering, translate research into product across the stack (Python, Postgres, React/TypeScript), and benchmark models to drive R&D decisions.

Develop, fine-tune, deploy, and monitor generative AI models; contribute to prompt engineering, RAG and hybrid search workflows; perform data preprocessing, feature engineering, API development; collaborate on integration, testing, code reviews, documentation, and ensure AI compliance and responsible-AI practices.

The AI Enablement Engineer leads programs for engineering teams to integrate AI, teaches best practices, and develops scalable learning models.

Lead the design and development of AI solutions for clients, implementing language models and frameworks, mentoring engineers, and evolving internal AI platforms.

The Principal AI Engineer will define AI architecture, lead teams, develop solutions, and mentor engineers to enhance enterprise AI systems.

The Full Stack AI Engineer will develop and deploy features using Next.js, Node.js, and Python, integrate AI APIs, and enhance user experience for creative automation tools.

Build and deploy AI systems for investment insights, focusing on ML and LLM-driven solutions, while ensuring high-quality data flow and outcomes.

Design, build, and ship production LLM-based systems and agentic workflows. Develop core learning libraries, human-in-the-loop feedback loops, confidence scoring, and scalable agent orchestration. Work with enterprise customers to prototype, deploy, and generalize solutions back into the platform.

Lead operation and maintenance of vulnerability management programs and tooling, refine detection and triage processes, collaborate with engineering on remediation, generate compliance reports, participate in incident investigations, automate security workflows, and improve vulnerability management documentation and processes.

Design, build, and deploy AI-powered solutions (LLMs, RAG, agents) to improve productivity and operational efficiency. Partner with business teams to define use cases, integrate AI with enterprise systems, create production-ready prototypes, and ensure solutions meet governance, security, and responsible AI standards.

The Senior AI Engineer will design and implement AI systems, focusing on production-grade solutions using LLMs and agentic systems to meet business needs.

Build and deploy client-facing agentic cybersecurity solutions: compose red-team/blue-team workflows, configure harnesses for cloud defense, vulnerability scanning and pen-testing, design context engineering and multi-agent orchestration, turn prototypes into production services, iterate with client feedback, and collaborate with pentesters and SWE-Cyber for accuracy and platform support.

Early-career AI engineer who ships production features rapidly using AI-augmented workflows. Own end-to-end features, prototype and evaluate LLM-driven solutions, collaborate with PMs and customer teams, pair with senior engineers, and maintain clear, tested, maintainable code while measuring impact.

Architect and implement scalable generative-AI solutions for enterprise document workflows. Own end-to-end delivery from customer discovery through deployment, build advanced extraction and automation systems, ensure privacy/security by design, mentor engineers, and collaborate with product and commercial teams to drive customer adoption and measurable business value.

Build, test, and ship LLM-powered, agentic AI solutions (RAG, tool-augmented agents) into enterprise workflows. Implement retrieval pipelines, observability, guardrails, CI/CD, and instrumentation; collaborate with stakeholders and deliver reusable patterns and handovers.

Design and implement large-scale AI/ML systems using LLMs and RAG. Develop data pipelines, optimize models, and collaborate with teams on actionable intelligence solutions.

The AI Engineer will develop the AI infrastructure, build approval workflows, and create intelligent collections agents, ensuring product reliability and customer satisfaction.

The role involves building and shipping production software, integrating AI tools, and developing internal applications to enhance operational efficiency and decision-making in a complex data-rich environment.

The Generative AI Engineer will design and implement AI solutions, focusing on model fine-tuning, prompt engineering, and secure deployment, while collaborating with cybersecurity specialists.

The role involves designing, developing, and supporting cloud and AI solutions primarily on Azure, including automation and integration components, while ensuring security and compliance.

Design, build, and maintain services and infrastructure for AI-powered agents. Develop Python backend services and tested APIs, support React front-end integrations, work with MySQL, implement RAG and vector DBs, apply prompt engineering, optimise LLM interactions, and monitor production reliability and performance.