Top AI Jobs in London

Own and improve transaction enrichment pipelines: form hypotheses, analyze performance with SQL/Python, prototype enrichment experiments using AI/LLMs, run structured evaluations, and partner with Product and Engineering to embed long-term improvements.

Lead a small AI-focused engineering team to design, build, and deploy production-grade AI-driven features and services. Contribute hands-on to coding, debugging, testing and integrating ML models into scalable microservice architectures. Define technical direction, tooling, standards, and mentor engineers while collaborating with Product, Architecture, and Data teams.

Evaluate AI-generated coding interactions, assess quality of engineering judgments, provide feedback, and define standards for AI coding agents. Comfortable making subjective judgments about engineering quality.

Lead technical pre-sales for enterprise AI: engage C-suite, design secure multi-cloud AI architectures, run workshops, build POCs, present demos, influence commercial strategy, and ensure smooth handover to delivery.

Design, build, and deploy production-grade ML models and recommendation systems, champion LLM use, optimise search and ranking, run A/B tests and statistical evaluations, and collaborate with engineering to integrate models into product infrastructure.

The Forward Deployed Product Associate will own end-to-end platform implementation for enterprise clients, analyze documents, design AI frameworks, automate processes, and collaborate with the product team for innovations and client insights.

Own and deliver AI initiatives end-to-end within the AI Centre of Excellence: translate business problems into AI use cases, build proofs-of-concept, design scalable solutions, ensure risk/compliance alignment, engage and coach stakeholders, and contribute to CoE standards and adoption.

Early-career role within the AI Centre of Excellence supporting AI use-case discovery, POC delivery, prompt engineering, Power Platform automations and Copilot Studio agents. Perform data preparation, testing, documentation, stakeholder engagement and compliance checks while learning tools, achieving certifications and rotating across CoE activities to deliver measurable business value.

Support planning, building, QA and deployment of CRM campaigns across email, push, SMS and in-app; manage journeys in Braze; use Movable Ink for dynamic content; apply AI and automation for personalization and optimization; analyze performance in Looker; support mobile app CRM, testing, and lifecycle optimization; deliver insights and streamline processes.

Build and ship production-grade agentic AI systems and LLM-powered features. Architect RAG pipelines over sensitive financial data, contribute shared AI infrastructure, own production reliability and safety, and collaborate with product and design to deliver customer-focused outcomes in a regulated environment.

Build and operate production agentic AI systems and LLM-powered features. Implement RAG pipelines, extend shared AI infrastructure, monitor and debug production models, and collaborate with product and design to deliver secure, reliable AI capabilities in a regulated financial environment.

Design, build, and operate production-grade agentic AI and LLM-powered features and RAG pipelines over sensitive financial data. Collaborate with product and design, contribute shared AI infrastructure (LLM services, orchestration, evaluation), and own reliability, security, auditability, and compliance in production.

Lead strategy and roadmap for AI platform tools, integrations, APIs, gateways, and agentic capabilities. Partner with engineering, data science, and partners to build reusable services, drive GenAI/agentic use cases, define metrics, and balance short-term delivery with long-term scalability and adoption across Amex's digital ecosystem.

The AI Research Engineer will develop AI models to enhance product autonomy, analyze extensive data, and deliver impactful solutions, driving innovative product features.

Manage AI tooling operations, ensuring reliability and performance of AI tools. Drive improvements and uphold technical standards across the AI stack as technology evolves.

As a Senior AI Engineer at Savanta, you will develop production-grade AI applications using C#, .NET, and Azure while collaborating with cross-functional teams to implement AI-driven features and enhance engineering capabilities.

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.

Lead product execution for Ping Identity's Identity for AI solution: define strategy, prioritize features, gather market and customer requirements, produce technical requirements, manage roadmap and backlog, collaborate with engineering, design, sales and marketing, enable go-to-market, and leverage AI tools to improve product workflows and delivery.

Lead end-to-end deployment and adaptation of LLM-based systems in humanitarian program contexts. Configure prompts, workflows, and integrations; test and red-team for safety; collect user feedback; train field teams; iterate on deployments; translate field insights into product improvements and reusable deployment frameworks to scale impact.

Lead architecture and delivery of production-grade ML and GenAI solutions on Databricks, support Solution Architects in pre-sales and technical deep-dives, build MVPs, design RAG and LLM-based systems, mentor teams, produce technical content, and drive platform adoption through trainings and events.

As a Senior AI Engineer, you will develop AI solutions, integrate models, and collaborate with teams to explore emerging AI frameworks and technologies. Responsibilities include working on client projects, employing agile methodologies, and contributing to an innovative tech community.

Lead AI transformation initiatives for Fortune 100 accounts, focusing on strategic account management, change management, and C-suite relationships to drive AI adoption and measurable business impact.

The AI Product Manager will define product vision and strategy, manage roadmaps, engage with stakeholders, develop go-to-market strategies, and track performance metrics for a cloud services platform focused on AI/ML.

The Head of Regulatory Affairs will lead global regulatory strategies for Tether Data, focusing on AI and P2P technologies, promoting compliance and advocacy with regulatory bodies.

The role focuses on engaging the developer community to drive adoption of Tether's technology through advocacy, technical content creation, community building, and collaboration with cross-functional teams. Responsibilities also include presenting at events and fostering feedback integration into product development.