Top AI Jobs in London

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 AI Research Engineer will research and develop novel model architectures, adapt open-source models, and contribute to the technical strategy and culture of the team.

The role requires working closely with customers to design AI-powered solutions, translating business problems into technical plans, and leading solution implementation.

The role involves developing new AI model architectures and adapting existing models, conducting experiments, and contributing to technical strategy in a high-growth research environment.

The AI Solution Engineer will design and implement AI-powered solutions for customers, translating business issues into technical solutions, and collaborating with stakeholders to ensure success.

The AI Engineer will create AI-driven solutions for commercial operations, leveraging ML and analytics to optimize workflows and decision-making. This role involves building production systems, managing commercial data infrastructures, and collaborating with sales and marketing teams for strategic improvements.

The role involves applying diffusion techniques and developing AI models to enhance 3D reconstruction pipelines for various industries.

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.

As a Founding Product Engineer at Nexcade AI, you will develop AI-driven automation solutions, build full-stack features, and collaborate directly with customers to address their operational needs.

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

The role involves designing, implementing, and delivering AI/ML solutions, developing machine learning models for scientific tasks, and collaborating with experts for data processes.

The Applied AI Engineer will onboard customers, deploy AI applications, and collaborate with teams to resolve technical challenges and drive technological transformation.

As a Software Engineer for AI Product at Figma, you'll build collaborative tools, lead AI projects, and work cross-functionally to enhance design accessibility and usability.

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.

Drive research and engineering for large-scale LLM and multi-modal pre-training: design architectures, curate massive datasets, run distributed training on multi-node GPU clusters, optimize model efficiency and alignment, debug long training runs, and scale distributed training systems to improve cross-modal performance.

Build production-grade, scalable React/TypeScript front-end applications and component libraries for AI-powered products. Architect client-side systems, optimise performance and accessibility (WCAG), establish testing and CI/CD practices, integrate APIs and real-time data, and mentor other engineers to deliver polished, enterprise-grade user experiences.

Lead customer-facing product efforts to shape PatSnap's AI-powered patent drafting solution. Advise patent professionals, run demos, workshops and pilots, gather feedback, and translate practitioner workflows into product features. Partner with Product and Engineering to validate capabilities, prioritize enhancements, and drive enterprise adoption alongside Sales and Customer Success.

Lead end-to-end client engagements for AI solution deployments in CPG/retail, manage cross-functional teams, advise on AI integration and change management, oversee deployment lifecycle, measure KPIs and adoption, and maintain senior stakeholder relationships to ensure business value realization.

Lead cross-functional engineering teams to design, deliver, and evolve cloud-native, event-driven insurance applications. Own architecture, roadmap, and delivery for policy, claims, underwriting, and compliance systems while ensuring regulatory adherence, vendor management, Agile/DevSecOps practices, and engineering KPIs.

Build and operate production-grade, low-latency Go microservices and developer tools for enterprise-scale AI platforms. Design distributed systems, integrate secrets and identity, implement observability and CI/CD, mentor engineers, and deliver scalable APIs and infrastructure to support LLM-powered applications.

Lead IRC's AI governance and enterprise AI projects—from intake, high-risk reviews, and policy implementation to cross-functional project delivery. Coordinate reviewers, maintain audit trails and guidance, manage project plans, sprints, testing, rollouts, and change management. Communicate status to senior leadership, surface risks, and drive responsible AI adoption across a global humanitarian organization.

Manage and build Turner & Townsend's AI governance program and support global privacy/data protection. Maintain AI and data inventories, improve data retention/destruction practices, run privacy and data governance training, assess risks, implement solutions, and liaise with regional and central stakeholders and external advisors to ensure compliance with AI and data protection regulations.

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.