Top AI Jobs in London

Own end-to-end design, build, deploy, and iterate on production AI systems that improve lead quality, reduce refunds, and automate workflows. Ship customer-facing AI features, agentic workflows, retrieval and context layers, reliable event-driven automations, evaluation datasets and monitoring, and reusable components while connecting technical decisions to business KPIs.

Design, build, and maintain developer tooling for the MAX AI inference stack, including profilers, tracers, debuggers, dashboards, and agent-native tools. Integrate tooling across MAX, Mojo, and driver APIs, collaborate with kernel/model/serving engineers, and drive performance analysis, debugging, and observability to improve developer productivity and production reliability.

The AI Platform Engineer leads the development of production AI agents and components, collaborates on AI implementations, and maintains AI systems for reliability and observability.

Design, build, deploy, and optimize AI/ML models and pipelines (including LLMs and RAG). Integrate models into production, work with cross-functional teams, ensure monitoring and compliance, and contribute to scalable AI systems and automation.

Lead engineering to shift GTM from no-code automation to code-first, AI-agent-driven systems. Design scalable backend pipelines, integrate CRMs/APIs, build reusable agent frameworks, ensure reliability and observability, and hire/mentor a distributed engineering team to deliver production GTM infrastructure.

Design, build, fine-tune, and deploy production-grade AI and ML systems (LLMs, RAG). Develop scalable APIs, integrate AI into business systems, monitor model performance, and collaborate with cross-functional teams.

Lead high-volume outbound prospecting, run discovery calls, qualify and manage high-ticket opportunities through the full sales cycle, book and conduct meetings, handle objections, collaborate with founders/sales leadership, and consistently meet outreach, meeting, and revenue KPIs.

The AI Data Expert will evaluate AI outputs, provide cultural insights, generate content, and ensure quality by applying evaluation guidelines and offering clear feedback.

The role involves evaluating AI outputs, providing annotations, and generating culturally relevant content while ensuring quality guidelines are met.

As an AI Engineer, you'll design AI tools for authors, enhance internal workflows, and build tools for AI development, collaborating with teams to identify AI opportunities.

Design and build workflows using node-based AI systems for video and image generation. Collaborate with teams to enhance AI-driven processes and create demos for various stakeholders.

The Senior Director Analyst for AI Cybersecurity will provide expert analysis and guidance on leveraging AI in cybersecurity for clients, driving innovation and impact in their operations.

As a Curriculum Manager, you will manage the content development lifecycle, collaborate with instructors, and improve data science curriculum, ensuring technical accuracy and pedagogical effectiveness.

Design and ship a 14-domain skills taxonomy and SDK/CLI tooling, operate the MCP server, integrate agent protocols, improve LLM grounding for crypto, run developer hackathons, and produce technical content to grow the ecosystem.

The Principal AI Engineer will build and improve the core AI tutoring system, design evaluation methods, and collaborate on pedagogical goals, driving innovation in learner experiences.

Responsible for building and evolving an AI tutoring system, running experiments, collaborating with teams, and ensuring quality in model behaviors.

The Curriculum Manager will oversee the content development lifecycle, recruit instructors, design curriculum, assess course performance, and improve data science and engineering content.

Build and evolve an AI tutoring system, run evaluations, design software, collaborate with teams, and ensure quality through testing and refinement.

As a Principal AI Engineer, you'll build and evolve AI tutoring systems, run experiments for learning effectiveness, design software, collaborate across teams, and prototype AI interactions.

Lead AI strategy for high-value enterprise accounts: advise C-level stakeholders, shape transformation roadmaps and business cases, influence deal strategy with executive leadership, structure engagements and proposals, run workshops and discovery sessions, and collaborate with product, engineering, GTM and delivery teams to align solutions and mentor internal teams on strategic storytelling and engagement design.

Develop and maintain an AI-driven pipeline to auto-generate, process, and publish real-life and digital quests. Integrate AI frameworks, design scalable automation workflows, analyze user data to improve generation quality, build API integrations, participate in architecture and documentation, test with pytest/unittest, and collaborate with cross-functional teams to validate LLM outputs against real-world data.

Seeking detail-oriented reviewers for AI training projects, evaluating outputs, generating content, and ensuring cultural relevance. Requires strong analytical skills and attention to detail.

Evaluate and review AI outputs, generate or assess content, and ensure cultural relevance and accuracy in various media for AI projects.

As a Software Engineer at Euphoric, you'll develop AI-driven features, collaborate across the tech stack, maintain quality code, and contribute to an innovative benefits platform.

Design and build a production multi-agent harness and MCP integrations that operate across ERPs, CRMs, and business tools. Own end-to-end production concerns (reliability, observability, permissions, safe workflow execution), scope the product, make architecture decisions, and ship features working closely with CTO, product, engineering, and design. Stay current with agent frameworks and use tools like Claude Code in development.