Top Tech Jobs & Startup Jobs in London

Lead client product engagements across discovery, strategy, digital transformation, delivery, and iteration. Guide senior stakeholders toward customer-focused outcomes, shape product management practices, and coach product managers. Apply service blueprinting, customer journey mapping, research, data, web and mobile knowledge, and practical AI experience—including agents, orchestration, and autonomous processes—to develop valuable products and services for enterprise clients.

Lead client product engagements, define product strategies, guide digital transformation, and oversee product development from discovery through delivery. Lead, coach, mentor, recruit, and support Product Managers while improving product practices and career pathways. Build trusted client relationships, remove blockers, support resourcing, and apply data, AI, research, and product management frameworks to deliver valuable customer-focused outcomes.

Senior Software Engineer responsible for designing scalable Java and Spring backend systems, developing secure REST APIs, and contributing to Vue/TypeScript applications. The role includes architectural leadership, technical decision-making, automated testing, CI/CD, cloud development, mentoring engineers, client collaboration, and delivery across multiple initiatives. The engineer will also evaluate emerging technologies, promote automation, and help adopt responsible AI practices to improve engineering effectiveness.

Senior AWS consulting leader advising enterprise clients on cloud, data and AI strategy. Lead discovery workshops, shape large-scale transformation programmes, design cloud-native roadmaps, support pre-sales, mentor architects, represent the firm externally, and ensure strategic intent translates into delivery.

Deliver and migrate production ML data pipelines from Databricks to an AWS SageMaker MLOps platform. Build feature engineering pipelines and feature store integrations, ensure parity/testing with Databricks outputs, manage storage/permissions/IAM, deploy via CI/CD and IaC, document runbooks, and collaborate with engineering, AWS ProServe, and client teams in a regulated iGaming environment.

Lead the adoption of AI-native software development practices as a hands-on Principal Engineer. Mentor engineers in tools such as GitHub Copilot, Claude Code, Codex, Cline, Kiro, and Cursor; introduce innovative workflows; solve complex technical problems; and collaborate with engineering and product leaders to translate AI-driven productivity and capabilities into product value. The role requires strong backend development skills, technical leadership, communication, and practical experience with generative AI tools.

Senior Software Engineer responsible for advancing AI-assisted software development across engineering teams. The role combines hands-on backend coding with mentoring, code reviews, technical leadership, workflow innovation, and adoption of tools such as GitHub Copilot, Claude Code, Codex, Cline, Kiro, and Cursor. The engineer will demonstrate AI-powered development practices, collaborate with technical and product stakeholders, and communicate productivity and product-value improvements.

Design and maintain scalable Java backend systems, REST APIs, microservices, and distributed architectures. Lead technical and architectural decisions, promote testing and automation, mentor engineers, collaborate with clients and cross-functional teams, and evaluate emerging technologies including AI to improve engineering delivery.

Lead technical direction for an AI platform connecting workloads to multiple LLM providers. Build API gateway and routing infrastructure, agent orchestration, capability lifecycle tooling, access controls, API key management, caching, cost and latency optimization, adoption analytics, and trust, safety, and governance controls. Define API standards and promotion workflows while supporting auditable, scalable AI services across client engagements.

Manage workforce allocation across consulting, engineering, product, design, delivery, data, and AI teams. Match employee skills and availability to client demand, optimize utilization, manage capacity and staffing risks, coordinate hiring needs, resolve resource conflicts, support revenue forecasting, monitor project margins, and provide workforce analytics and recommendations to leadership.