Top AI Jobs in London

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, build and deploy production-ready AI/ML solutions (including NLP, computer vision and generative AI) for UK public sector clients. Implement MLOps, develop scalable data pipelines and API-driven services, integrate Azure AI/LLM platforms, ensure responsible AI practices, and support proposals, PoCs and knowledge sharing across consulting teams.

Independent full-cycle recruiter managing sourcing, client engagement, offer negotiation, and placements using AI-driven tools. Acts as commercial advisor, provides market insights, and maintains self-directed billing and activity in a results-only, remote environment.

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.

As a Full Stack Developer on the AI Team, you will build production-ready backend and full-stack features, integrating AI functionality into the think-cell product while collaborating with C++ and AI engineers.

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.

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

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.

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 Oyster's data platform and AI strategy, centralize AI initiatives into production systems, build scalable data and MLOps infrastructure, modernize knowledge architecture and semantic search, partner cross-functionally to embed AI into products and workflows, enforce tooling standards and governance, and drive organizational adoption and change management for AI-assisted operations.

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.

Lead discovery, design and delivery of data modernisation and migration projects. Design data lakes/warehouses/lakehouses and landing zones, advise on data strategy, governance and quality, implement Microsoft/Azure and Databricks platforms, support AI/ML initiatives, run workshops, produce technical documentation, contribute reusable assets, and support pre-sales and practice development.

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.

Lead end-to-end onboarding for enterprise customers: run discovery, design solutions, configure the product, build integrations, manage risks/escalations, and adopt AI-driven workflows to automate tasks and accelerate time-to-value while collaborating with product and engineering.

The Senior AI Implementation Manager will lead customer onboarding, manage integrations, and ensure value delivery through AI-driven workflows with a consultative approach.

The Director of Product Management - Data & AI Platform defines and drives the strategy and roadmap for Gentrack's Data & AI initiatives, focusing on platform leadership, AI capabilities, and cross-functional collaboration to enhance customer value.