Top Tech Jobs & Startup Jobs in London

Lead an infrastructure engineering team to design, deploy, and operate scalable, secure production environments for AI-driven applications. Define roadmap, maintain SLAs/SLOs, build CI/CD and IaC pipelines, manage on-prem and cloud Kubernetes deployments, improve developer tooling, and drive incident response and monitoring best practices while mentoring engineers.

Lead development of production AI behavior, governance, and MLOps standards for high-risk public-sector systems. Architect and validate safety-focused AI components, build reusable agent and evaluation capabilities, advise executive clients on AI strategy, resolve severe model-safety incidents, and coach senior engineers while shaping the technical roadmap and recruitment.

Build and scale an enterprise Generative AI platform. Own large product areas across backend and frontend, develop reliable Python backend services, integrate LLMs, vector databases, and AI infrastructure, work with distributed systems and data pipelines, and ship features quickly while collaborating with product, ML, and infrastructure teams.

Build and operate core retrieval and knowledge representation systems for a generative AI platform: design RAG pipelines, embeddings, indexing, vector-store integrations, knowledge graphs/ontologies, evaluation frameworks, and production ML backend services while collaborating across product, ML, and infra teams and shipping enterprise-grade features.

Build and run EMEA GTM onboarding, centralize and maintain a sales knowledge base, deliver recurring enablement programs, and support priority deals by creating reusable playbooks and field-ready materials to help sellers communicate Scale's AI capabilities.

Manage engineering teams to deliver AI-driven applications, oversee product lifecycle, mentor engineers, and collaborate cross-functionally.

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.

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.

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.