Top AI Engineer Jobs in London

Lead pre-sales technical evaluations for LogicMonitor's Edwin AI: run discovery, demos, and proof-of-value; configure use cases, prompts, dashboards; train sales and customer-facing teams; translate customer challenges into Edwin AI solutions; document requirements and outcomes in Salesforce; drive successful evaluations and resolve technical obstacles.

Design and ship consumer-facing generative AI and AR features for image/video generation and editing. Prototype models, integrate ML into production pipelines, collaborate with Product/Design/Engineering, evaluate open-source models and APIs, and iterate via A/B testing and user feedback.

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.

Design and build GitLab Duo CLI features in TypeScript, shape AI-assisted developer experiences, improve CLI reliability, observability, and performance, collaborate across Developer Clients, and provide technical leadership and mentorship.

Design and deliver end-to-end features for DAP onboarding and repository/background flows. Build autonomous and scheduled agents that act on customer codebases, improve onboarding experience, collaborate on shared interfaces, review code and designs, and contribute to an async-first, distributed team's technical quality and ownership culture.

Design, build, and operate the high-availability event and trigger system that links GitLab and third-party events to AI-powered Duo Flows. Work in GitLab's Rails monolith, scale for high throughput, influence architecture, add trigger types, collaborate cross-functionally, and participate in Tier 2/3 on-call rotations to troubleshoot production issues.

Build secure, scalable AI/ML platforms and applications to productionize research. Collaborate with AI researchers and data scientists, implement CI/CD and IaC, support experimentation environments, automate remediation, mentor junior engineers, and promote secure, responsible AI development practices.

Design, build, and maintain AI agents and automated workflows for marketing. Identify automation opportunities, deploy and monitor agents, integrate with marketing tools, and report efficiency and business impact. Ensure data quality, privacy, and documentation, and enable marketing teams to adopt automations.

As an Applied AI Engineer, you will build AI applications for public sector clients, create and evaluate datasets, and collaborate with teams to address challenges using AI solutions.

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.

Lead developer engagement for firmwide developer tools to drive safe, practical adoption of AI coding tools. Run demos, workshops, and enablement; create guidance, examples, and playbooks; gather feedback; partner with platform, risk, and engineering leaders to scale adoption across a regulated enterprise.

Build end-to-end AI-first product features, design scalable APIs and frontends with React/TypeScript, integrate LLMs and AI agents, collaborate with founders and customers, and establish engineering culture and infrastructure.

Design, build and deploy agentic AI features and LLM-driven systems for secure, compliant environments. Integrate AI across backend and UI, optimise models (including perception/CLIP/CLAP), document for compliance, and deliver robust production solutions.

As an AI Deployment Engineer, you will work with startups to optimize AI systems, prototype solutions, and improve model behavior while collaborating closely with product and research teams.

Design and ship production-grade AI features into established C# .NET products: prompt and context design, LLM integration, error handling, fallbacks, monitoring, and structured evaluation. Collaborate with product owners and engineers, prototype quickly, harden features, and document work so teams can maintain and adopt AI capabilities safely and effectively.

Build and ship production-grade AI features inside established C# .NET products: prompt and context design, LLM integration, evaluation, error handling, monitoring, and collaboration with product and engineering teams to deliver accurate, safe, measurable AI capabilities.

Deploy and integrate Latent Labs' generative biology models into customer environments. Lead end-to-end technical deployments, build production-grade APIs, data pipelines and model-serving infrastructure, work on-site with pharma/biotech partners, ensure enterprise security and reliability, gather customer feedback, and document integrations while collaborating with product and research teams.

As a Senior Python Engineer, you'll design and build the core infrastructure for AI forecasting systems, integrating data ingestion and reasoning mechanisms while contributing to technical strategy and team growth.

Lead the evolution of Tenable's multilingual delivery platform toward AI/LLM-led localization. Design event-driven, API-first translation pipelines, integrate LLMs into production workflows, extend AI-led delivery across content types, define standards and governance, build AI-powered reporting, and deliver key initiatives while coordinating distributed and contracted engineering partners.

Design, build, and operate a secure, high-performance sandboxing platform and client library for code execution across containerized and virtualized environments. Ensure strong isolation, optimize latency and resource use, debug and reduce errors, respond to incidents, and drive roadmap and architecture reviews while partnering with internal users.

Lead design, governance and delivery of enterprise-grade AI capabilities for Global Markets. Define AI platform standards, reusable components, risk controls and release governance. Build RAG frameworks, evaluation harnesses, connectors and monitoring; enable citizen and function-led AI safely; partner with Risk, Cyber, Legal and business stakeholders to ensure compliant, auditable, and resilient AI operations with measurable business benefits.

Lead CMS and web platform modernisation efforts, prototype AI/agentic POCs, and support the Principal Engineer to shape technical direction. Investigate where AI adds value, refocus the CMS team on higher-value marketing work, improve scalability and management, and collaborate with stakeholders to define pragmatic technical approaches and roadmap.

Build, deploy, and maintain AI-powered web applications for government and industrial customers. Work end-to-end: define product specs with customers, implement front-end and back-end systems, integrate data pipelines and sensor networks, optimize performance and reliability, and support deployed systems globally. Collaborate with cross-functional teams, mentor junior engineers, and travel on-site to deliver production-grade solutions.

Deploy and optimize LLM-based solutions for real-world government, healthcare, and energy problems. Build scalable data pipelines, productionize models (RAG/agents), monitor performance, engage stakeholders including government officials, and collaborate with cross-functional teams to deliver impactful AI products.

Design, train, evaluate and deploy robust deep learning models from sensor input to user interface; integrate models into cloud and edge systems; work with customers to define problems; document, monitor and ensure safe, secure production AI solutions.