Top Tech Jobs & Startup Jobs in London

Lead and own EMEA-specific assurance and certification programs (GCC, UK, EU), map controls, collect evidence, manage gaps and auditors, extend global certifications (SOC2, ISO), support customer assurance, legal and procurement compliance, and coordinate audits and regional regulatory engagement.

The Staff Technical Product Manager will own the product roadmap for Global Defense, design AI products, collaborate with engineers, and understand defense workflows to drive product outcomes.

Lead the Forward Deployed Engineering team, overseeing AI deployment and production excellence for major enterprise accounts while enhancing team capabilities and organizational standards.

As a Machine Learning Engineer, you'll train and deploy ML models for enterprise clients, work on deep learning solutions, and interface with product teams to enhance AI applications.

As a Solutions Engineer, you'll engage with customers to design AI solutions, deliver demos, and collaborate with teams, ensuring technical needs are met.

Design and implement identity infrastructure for authentication and authorization across enterprise systems. Build SSO, MFA, federated identity, and authorization systems (ReBAC/ABAC/RBAC). Implement governance policies for compliance (NIST, SOC2, ISO27001), and advise stakeholders on identity management best practices.

The Product Manager will lead the development of AI solutions, manage cross-functional teams, and drive product strategy, focusing on customer needs and enterprise applications of ML-powered products.

Lead a team of Product Managers to integrate Scale products into complex enterprise and government environments. Hire and mentor PMs, translate bespoke field deployments into scalable product strategy, partner with Sales/GTM and EPD, unblock high-priority deployments, and ensure the voice of the field informs roadmap decisions.

Lead strategic planning and execution for the Scale Generative AI Platform, owning technical scoping, architecture, and production launches. Coordinate cross-functional teams (platform engineering, Core ML, Research, Product), translate infrastructure metrics into roadmaps, mitigate deployment risks, define SLOs, drive developer velocity, and report adoption and reliability metrics to executive leadership to ensure scalable, secure, production-grade GenAI infrastructure.

Own end-to-end delivery of enterprise AI programs: manage timelines, risks, dependencies, and cross-functional integration. Translate technical complexity for engineering and executives, modernize agile workflows, and define program health metrics to drive adoption and scalable, reliable agentic solutions.