Top AI Jobs in London

Drive enterprise revenue for Provenir’s Agentic AI Platform, initially expanding within existing clients and then acquiring new-logo customers. Build expertise in fraud and financial crime, lead complex 6–12+ month sales cycles, develop value-based business cases, engage C-level stakeholders, coordinate cross-functional teams, negotiate multi-year agreements, and maintain accurate pipeline forecasting. The role targets regulated financial services organizations and high-value contracts of approximately $1M+ annually.

Lead the vision, strategy, and roadmap for Elliptic’s compliance product portfolio, including screening, monitoring, investigations, risk configuration, and agentic AI capabilities. Manage and develop product managers while remaining hands-on with complex product challenges. Partner closely with customers, prioritize zero-to-one initiatives, ensure rigorous execution, and build auditable, explainable products for regulated, high-stakes financial crime compliance environments.

Own a core AI product by translating client and business needs into validated specifications, AI-assisted prototypes, sprint-ready backlogs, user stories, acceptance criteria, and product documentation. Manage Azure DevOps backlog processes, support Agile ceremonies, incorporate user feedback, and contribute to release communications and go-to-market materials. Collaborate with product, delivery, technical, engineering, and client stakeholders while applying practical knowledge of GenAI, LLMs, RAG, agentic AI, SaaS development, and release management.

Leads the strategic vision, lifecycle, roadmap, governance, and commercial execution of enterprise decisioning platforms. Responsibilities include developing automated decision engines and workflow tools, integrating cloud-native architecture and AI, conducting market and customer research, managing product performance and revenue, and ensuring regulatory compliance. The role requires experience with B2B SaaS, risk or credit decisioning, automated workflows, cloud platforms, APIs, and AI-enabled products.

Lead the people strategy for Smiths Detection’s global IT and Digital transformation. Partner with the CIO and senior technology leaders on workforce planning, organizational design, talent strategies, capability building, succession planning, change management, and organizational transitions. Support the creation of a standalone global IT function and growth of Digital teams across software, data, AI, and technology. Provide HR governance, leadership coaching, employee relations oversight, and workforce risk management across global operations.

Leads the transformation of release management across Product and Technology by modernizing governance, embedding automated risk-based controls, and enabling safe, data-driven deployments. Oversees release strategies, environment governance, customer onboarding readiness, release intelligence, observability, progressive delivery, and AI-native release practices. Builds and develops the release management function, drives change across engineering stakeholders, and secures investment for tooling, automation, telemetry, and platform improvements.

Lead end-to-end strategy and transformation workstreams for clients, from research and problem framing through recommendations and implementation. The role covers operating models, change roadmaps, AI adoption and governance, commercial cases, account growth, and practice development. Responsibilities include leading client relationships, managing budgets and scope, developing propositions, coaching colleagues, and translating strategic vision into measurable business outcomes.

Serve as the technical expert for industrial AI sales, building relationships with cement plant engineers and leaders. Analyze plant data, identify opportunities, lead technical discovery, create commercial proposals, handle objections, and ensure successful handoffs to deployment teams. Provide field feedback to product and machine learning teams, improve the pre-sales process, and travel to plants and conferences approximately one week per month.

Build and deploy AI tools and automated workflows for People and Talent operations. Own people reporting and analytics, including retention, attrition, engagement, and hiring dashboards. Maintain accurate HRIS data, support Lattice performance cycles and engagement surveys, analyze workforce insights, and improve onboarding, payroll data integrity, and performance processes. The role requires building user-facing AI solutions, working with real datasets, protecting confidential information, and operating effectively in an ambiguous, fast-growing environment.

Lead AI architecture and engineering for enterprise agentic AI systems. Define standards for RAG, agents, orchestration, evaluation, security, and governance; provide hands-on technical leadership, mentor engineers, and align cross-functional stakeholders to deliver secure, compliant AI solutions.

Build full-stack AI-enabled applications and backend services integrating MCP servers, LLMs, RAG retrieval, and agent orchestration. Design reusable MCP tools/skills, implement secure RBAC, ensure observability, and prepare deployments for OpenShift/Kubernetes while collaborating across product and platform teams.

Lead and grow Nerdio’s EMEA SDR organization by hiring, coaching, and developing multilingual teams; owning pipeline targets; entering emerging markets; defining ICPs and territories; developing localized and partner-led strategies; analyzing conversion and activity data; forecasting; integrating AI into prospecting and coaching; and partnering with Sales, Marketing, Partners, and Sales Ops.

Own central FP&A at a high-growth AI company, including the driver-based company model, budgeting, reforecasts, monthly reporting, board materials, and capital allocation analysis. Build planning processes in Pigment, consolidate inputs across functions, and provide actionable financial recommendations to executives and the board. The role requires hands-on financial modeling, commercial judgment, unit economics expertise, planning-tool experience, SQL, and data warehouse fluency.

Design and deliver enterprise-grade machine learning systems and AI-powered applications for banking. Build scalable, secure, distributed applications and automated cloud, desktop, and ML pipelines. Apply MLOps practices for versioning, reproducibility, and observability while collaborating with cloud and site reliability engineering teams. Develop reusable libraries and business-critical, data-intensive solutions, aligning machine learning problems with business objectives. The role may include mentoring or people leadership.

Lead research and development of Transformer-based and time-series foundation models for systematic trading. Responsibilities include pre-training models from scratch on large-scale financial datasets, designing representations and self-supervised objectives, developing distributed training systems, fine-tuning models for trading applications, studying scaling and regime robustness, and evaluating economic performance through simulations and live-trading metrics.

Leads a team building secure, production-grade AI-driven software systems. Responsibilities include software architecture, Java or Python development, AI/ML integration, LLM and generative AI applications, algorithm validation, automated testing, CI/CD, cloud-native development, troubleshooting, and operational reliability. The role also establishes responsible AI practices, validates AI-assisted engineering outputs, mentors engineers, translates business requirements into technical roadmaps, and ensures timely delivery through Agile methodologies.

Lead delivery of a governed agentic AI platform portfolio supporting Markets Operations. Own release calendars, dependency maps, critical paths, risk resolution, migrations, decision records, and executive reporting. Build evidence-based metrics for delivery, platform health, business impact, and agent autonomy. Coordinate engineering, product, controls, design, and operations teams while ensuring safe production releases and audit-ready delivery evidence.

Lead the design and development of production-grade agentic AI applications for Markets Operations. Build reusable AI architecture patterns, orchestration frameworks, context management, evaluation pipelines, guardrails, APIs, infrastructure, and monitoring. Partner with researchers, engineers, data scientists, and operations stakeholders to deliver secure, reliable, compliant AI solutions. Drive continuous improvement, document technical decisions, influence architecture, and mentor engineers.

Lead AI controls enablement by translating AI risks into practical controls, partnering with Controls, Business, and Technology to design scalable solutions, perform risk reviews, implement controls, and advise senior stakeholders to ensure compliant AI adoption.

Leads country-level commercial performance, strategy execution, delivery quality, regulatory compliance, workforce planning, and cross-functional alignment. The role owns local entity performance within a shared P&L model, drives AI adoption, manages client and partner relationships, represents the company externally, and ensures global priorities are effectively adapted and delivered in the local market.

MBA Summer Associates join consulting teams for 8–12 weeks, contributing to real client projects and developing hands-on strategy consulting experience. Responsibilities include strategic analysis, creative problem-solving, teamwork, and applying AI-based solutions and data competencies to complex business challenges. Strong performers may receive full-time offers.

Leads technology policy consulting engagements and business development across Asia-Pacific. Advises technology-sector clients on public policy, regulation, politics, geopolitics, and commercial strategy, with emphasis on areas such as AI, online safety, data governance, data centres, digital competition, and telecommunications. Responsibilities include researching complex policy issues, developing strategic recommendations, managing projects and teams, engaging senior clients and stakeholders, and identifying commercially viable opportunities.

Analyze complex datasets, develop dashboards and reports, translate stakeholder requirements into data-driven solutions, and support analytical models and AI-enabled capabilities. The role involves collaborating with engineers and multidisciplinary Agile teams, ensuring data quality and documentation, presenting insights, and supporting UX/UI design within a secure Defence programme.

Own post-booking product areas for US credit cards, including payments, collections, credit limit increases, spending, and the mobile app. Run customer experiments, conduct research, collaborate with credit risk and data science, prototype solutions with AI, build automations, and launch improvements. The role requires comfort with ambiguity, data-driven decision-making, rapid testing, and hands-on execution across product, engineering, operations, legal, and compliance.

Own post-booking credit card product areas including payments, collections, credit limit increases, spending, and the mobile app. Run customer experiments, conduct research, use data and AI to test opportunities, collaborate with credit risk and data science, build automations, and deliver solutions with engineering, operations, legal, and compliance teams.