Top AI Jobs in London

Conduct independent, governance-focused research on AI scheming and loss-of-control risks; produce reports, papers, legal analyses; collaborate with technical teams, policymakers, and external researchers; mentor junior researchers and shape team strategy.

Contract AI Engineer to build an enterprise AI capability: design agentic workflows and Copilot extensions across Microsoft 365 and Salesforce, build production-ready agent solutions (connectors, monitoring, cost controls), translate sales methodology into real-time coaching and CRM insights, and collaborate with GTM leadership to drive behaviour change. Hybrid role in London for 4-6 months (3-4 days/week).

Design and implement AI-powered internal tools for GTM use cases, managing full lifecycle from data modeling to production. Collaborate closely with GTM teams to translate data into actionable insights with a focus on measurable business impact.

You will design, build and refine AI systems for legal applications, focusing on LLM agents and data evaluation frameworks.

The Senior Product Owner (Data / AI) will be responsible for leading the development of data-driven product domains, collaborating with analytics and AI teams, defining product strategies, and ensuring the execution and delivery of data & AI product features.

Fogsphere seeks a PhD-level AI/ML Researcher to develop innovative solutions in deep learning and computer vision, leading research efforts and collaborating with engineers to implement ideas.

Develop scalable cloud infrastructure and robust software solutions for AI/ML, collaborating with engineers and scientists to enhance scientific research.

Lead global deployment and adoption of the Liquid AI Solutions suite by developing and improving deployment tooling, processes, and playbooks. Manage Voice of Customer feedback, triage recurring issues, maintain prioritized backlogs, and coordinate cross-functional resolution. Track work in JIRA, support release readiness and testing, and deliver training to global client configuration and success teams to drive scalable, high-quality client outcomes.

Responsible for leading quality assurance across underwriting lines, improving testing strategies with automation, and mentoring QA teams to enhance delivery quality and efficiency.

The Applied AI Transformation Manager drives program delivery for strategic accounts, ensures value realization from AI projects, and builds customer trust through effective operations and communication. You'll manage complex enterprise relationships and support onboarding of AI solutions.

Build and scale shared AI platform foundations on Azure, focusing on agentic AI. Design templates, reference implementations, secure model access, LLMOps patterns, observability, CI/CD, and operational reliability while partnering with product, cloud, and security teams.

As an AI Software Developer, you'll create AI-driven solutions, collaborate with teams, gather requirements, and manage product deliverables in a financial context.

Uncountable seeks a Platform Engineer focused on Generative AI to develop AI-powered tools for scientific R&D, requiring fullstack development skills and a passion for advancing user needs.

The AI/ML Quantitative Research Manager leads research efforts in quantitative strategies, develops AI/ML models for trading signals, and collaborates with internal teams to enhance trading systems.

The AI & Automation Lead will oversee a team in delivering automation and AI solutions, providing technical guidance, ensuring quality, and engaging clients in various industries to support their transformation journeys.

Lead privacy and AI governance across EMEAPAC: implement and improve compliance frameworks, monitor regulation (including EU AI Act), manage DPIAs/RoPAs/DSARs, advise business and technical teams, run incident response, draft vendor data terms, deliver training, and support the Head of Regulatory Risk and DPO.

As a Staff Software Engineer at The Trade Desk, you will design, build, and deliver data-focused products, contribute to solution design, and mentor other engineers. You will work on large-scale distributed systems and collaborate in a diverse team environment to solve complex problems.

Develop intelligent agents for a materials discovery engine, orchestrating scientific workflows and integrating experimental design for sustainability solutions.

Build and evolve a reusable data and ML platform: implement IaC and CI/CD, develop Python/Spark components, support data/ML lifecycle and AgentOps, improve observability, enforce security and governance, and collaborate across engineering and data teams.

Lead data and AI product strategy: define data requirements, own data and AI initiatives end-to-end, write engineering-ready epics/stories, collaborate cross-functionally to build scalable data products, and drive analytics for LLM/agent interfaces.

Own end-to-end implementation of an AI-native benefits platform for enterprise clients, including on-site deployments and document data work. Perform document analysis and extraction, design AI evaluation frameworks, engineer prompts, build agentic AI workflows, track product analytics on production data, and gather customer insights to inform product development.

Support legal, risk, and compliance programs to prepare them for AI adoption by organizing data, consolidating sources, drafting process documentation, conducting research, building trackers and dashboards, quality-reviewing AI outputs, and documenting AI-enabled workflows under governance standards.

Lead the Business Travel product roadmap and deliver prototype-to-production features in an AI-first model. Manage client relationships, implementations, integrations (TMC/HRIS/APIs), and vendor partners. Drive data analysis, regulatory-compliant product design, stakeholder reporting, incident response, and RFP content, coordinating with legal, engineering, and senior leadership.

Build AI-driven automations and integrations to reduce manual work, collaborating with product and engineering. Use agentic AI tools to plan, build, test, and deploy full‑stack production software while engaging users, iterating on UX, and promoting continuous improvement.

Lead end-to-end deployments of generative AI solutions embedded with business teams: discovery, scoping, architecture, build, and production rollout. Develop LLM-powered applications, write production-grade frontend and backend code, feed field insights into the central AI platform, and drive adoption through measurement and stakeholder communication.