Top AI Jobs in London

Design and scale advanced analytics, statistical, machine learning, and AI solutions for Life Sciences customers across Europe. Integrate Veeva Data Cloud with healthcare datasets, build HCP precision-engagement models, translate technical insights into business value, collaborate with cross-functional teams, and document methodologies, architectures, and validation processes.

Lead client workstreams and support business growth across government, regulatory, political, and technology policy matters in the UK and Middle East. Responsibilities include developing engagement strategies, mapping stakeholders, drafting proposals and policy briefings, advising senior executives, presenting insights, managing client relationships, identifying commercial opportunities, and producing high-quality analysis and thought leadership across technology, AI, space, defence, cybersecurity, and digital regulation.

Leads the digital Product Group, owning product strategy, roadmap, incubation, development, launch, operations, governance, and commercial outcomes. Builds and manages teams of product managers, business analysts, and operations professionals. Partners with business, technology, and client-facing leaders to deliver valuable products, while championing practical AI adoption across product delivery and operations. Requires strong senior stakeholder management, commercial judgment, analytics, and modern product management expertise.

Supports strategy and business transformation projects for Telecom, Media, and Technology clients. Responsibilities include market research, forecasting, benchmarking, business plan assessment, financial modeling, client-ready analysis, workstream ownership, proposal development, and supervision of junior staff. The role requires translating complex findings into recommendations for senior client and investment committee stakeholders while managing deadlines, quality, and client relationships.

Define, architect, and lead delivery of machine learning and AI solutions. Support exploratory data analysis, proofs of concept, and the end-to-end data science lifecycle. Translate business problems into analytical and modeling solutions, communicate findings to technical and non-technical stakeholders, and provide specialist model delivery support. Design, develop, test, implement, and monitor models while tracking advances in data science and advising leadership on competitive capabilities.

Provide scientific leadership for evaluating foundation models and applying machine learning to genomics, drug development, and translational research. Partner with research, product, and business development teams to create customer-focused workflows, mentor junior colleagues, translate complex science for varied stakeholders, and guide rapid prototype-to-insight experimentation.

Lead development of high-performance Java applications for real-time FX risk management. Responsibilities include architecture, low-latency distributed systems, JVM optimization, coding, AI-assisted development, code reviews, testing, cloud deployment, production support, release ownership, and technical leadership without direct reports. The role works closely with quantitative analysts, traders, and business stakeholders while contributing to global risk technology strategy.

Leads an AI Controls Enablement team developing, evaluating, and scaling automated controls across Asset and Wealth Management. Translates AI behavior and risks into actionable control findings, oversees tool submissions, conducts simulations and red-team exercises, establishes governance standards, leads the AI Controls Council, and reports progress and impact to senior leadership. Partners with Controls, Technology, and business stakeholders to deliver compliant, sustainable AI solutions.

Build and productionize secure AI applications from prototypes, including Python services, APIs, data models, MCP integrations, testing, deployment, monitoring, authentication, and support. Evaluate AI behavior, manage production reliability and costs, and collaborate with Technology, security, infrastructure, and product teams. The role requires pragmatic engineering judgment, strong Python and SQL skills, and experience taking incomplete applications into production.

Define and own the quality bar for Spotify's AI voice models by designing evaluation rubrics, running qualitative and MOS-style campaigns, benchmarking against competitors, and turning findings into actionable recommendations for product, production, and ML teams.

Develop and support secure, scalable software for AI/ML data platforms. Responsibilities include Python architecture and development, cloud-native and containerized application delivery, code review, testing, troubleshooting, operational stability, and automation of recurring remediation. The role also promotes validated AI-assisted engineering practices and collaborates with product managers and data strategy teams. Preferred experience includes graph databases such as AWS Neptune and generative AI engineering pipelines.

The AI Enablement Intern at Providence will support AI solutions for investment teams, build workflows, drive adoption, and improve decision-making across portfolio companies.

Lead security investigations for AI systems used in scientific discovery. Develop threat models, test defenses through adversarial assessments and technical analysis, define security requirements, evaluate evidence, and drive improvements with Security, Safety, and engineering teams. The role addresses dangerous misuse, model and data compromise, deployment risks, and safeguards for increasingly capable AI systems.

Build and maintain software, services, data pipelines, and model integrations for AI safety evaluations, red teaming, mitigation experiments, and scientific AI research. Translate researcher needs into reliable tools, preserve reproducible experiment records, and own systems from prototyping through deployment, testing, monitoring, documentation, and improvement. Collaborate with AI and software engineering teams on shared infrastructure.

Develop and implement safety mitigations for frontier scientific AI models, agents, tools, and laboratory-connected workflows. Translate risk assessments and policy requirements into safeguards spanning training, classifiers, monitoring, access controls, and runtime interventions. Design experiments, evaluate robustness and legitimate-use impacts, investigate failures and distribution shifts, and integrate mitigations with model training, inference, platform, and evaluation teams.

Develops governed business intelligence solutions, including dashboards, semantic models, reports, and data visualizations, to support executive decision-making. Partners with product owners, engineers, architects, and business stakeholders to translate needs into analytical experiences. Mines data for trends, applies statistical analysis, supports AI-enabled analytics, and maintains consistent metric definitions. The role also emphasizes governance, risk management, controls, stakeholder communication, and user-friendly data products.

Leads Soho House’s global Member Support and Member Success functions, setting service strategy, operational standards, retention initiatives, and lifecycle engagement programs. Oversees global teams, outsourced partners, workforce planning, SLAs, escalations, budgets, and commercial outcomes. Drives automation, self-service, process redesign, voice-of-customer programs, and cross-functional collaboration to improve satisfaction, loyalty, lifetime value, and revenue while reducing churn.

Lead business development for InspireXT’s Databricks practice across the UK. Build Databricks ecosystem relationships, develop joint go-to-market initiatives, generate demand, prospect customers, maintain CRM pipelines, and support discovery sessions, proposals, demonstrations, RFPs, and commercial discussions. The role partners with Databricks, marketing, leadership, and delivery teams to create consulting, implementation, and managed services opportunities.

Lead design and delivery of production-grade ML and GenAI solutions on the Databricks platform. Architect end-to-end ML pipelines, optimize training/inference, implement MLOps/LLMOps, build MVPs for sales, influence product roadmap, mentor peers, and present technical content externally.

Lead public sector account growth across EMEA by meeting sales quotas, building pipeline, leveraging partners, cultivating senior client relationships, and closing complex enterprise deals. Develop customer and competitive insights, manage public sector sales processes, and provide product feedback to Product and Engineering teams. The role requires strong government or public sector credibility, stakeholder management, and experience navigating bids, partnerships, accounts, and internal processes.

Own the roadmap and strategy for AI- and data-powered advertising products spanning ad targeting, creative optimization, and measurement. Lead development and data science teams, translate strategy into prioritized backlogs, define user stories, and guide products from concept through deployment. Use SQL with Snowflake or BigQuery for hands-on analysis, validate product hypotheses, prototype ideas, and collaborate with technical and commercial stakeholders to deliver measurable advertiser value.

Advise lawyers and legal teams across EMEA on adopting Relativity’s AI products. Build customer relationships, support pre-sales demonstrations, enable post-sales onboarding and training, guide legal workflow transformation, and provide product feedback. Translate AI capabilities into practical legal use cases while partnering with sales, customer success, product, marketing, and engineering teams.

Supports the delivery of bespoke AI transformation projects for retail and consumer clients. Responsibilities include managing workstreams, gathering stakeholder and user needs, conducting open-source analysis, translating operational requirements into user stories, designing and testing workflows, collaborating with engineering teams, and contributing to strategy and internal capability development.

Leads the technology strategy, architecture, governance, and delivery of Legal AI, knowledge management, and document management platforms. Defines roadmaps, integrates platforms with Microsoft 365, SharePoint, iManage, and enterprise systems, and ensures secure, scalable solutions. Partners with architecture, cybersecurity, engineering, data, vendors, and business stakeholders to translate requirements into technical designs and investment decisions.

Leads and develops a distributed EMEA team of Applied AI Architects, setting pre-sales standards and supporting strategic digital-native customers. Responsibilities include AI adoption strategy, use-case scoping, proof-of-concepts, technical demonstrations, ROI validation, API and LLM architecture, regulatory and procurement guidance, cross-functional alignment, and executive customer engagement. The role also represents Anthropic in the European technology community and requires regular EMEA travel.