Top Tech Jobs & Startup Jobs in London

Owns technical direction and execution for major products and systems. Designs scalable, reliable architectures across backend, frontend, APIs, databases, and infrastructure; remains hands-on with coding, prototyping, reviews, debugging, and production support. Leads architecture decisions, resolves complex technical problems, improves engineering quality, drives critical initiatives, and mentors engineers across teams.

Lead an AI payments business end to end, owning P&L, strategy, product decisions, team building, execution, growth, partnerships, operations, revenue, and profitability. The role requires identifying customer and commercial opportunities, collaborating with product, engineering, and design teams, launching and improving products, and managing performance in a fast-paced, hands-on environment.

Leads BJAK’s UK business end to end, owning P&L, strategy, product direction, team building, execution, growth, revenue, partnerships, operations, and profitability. The role identifies customer and commercial opportunities, directs product launches, builds cross-functional teams, and remains accountable for business results from idea through scale.

Lead the wealth management app business end to end, owning P&L, strategy, product direction, team building, execution, growth, revenue, and profitability. Identify customer and commercial opportunities, partner with product, engineering, design, and operations teams to launch and scale products, and establish the partnerships and operating capabilities needed for success.

Leads the Travel FX business end to end, owning P&L, strategy, product development, team building, execution, growth, revenue, partnerships, operations, and profitability. The role requires identifying customer and commercial opportunities, deciding which products to build, coordinating with product, engineering, and design teams, and scaling the business while managing performance and delivering measurable results.

Lead an AI-native email app business end to end, owning P&L, strategy, product direction, team building, execution, growth, revenue, partnerships, operations, and profitability. Identify customer and commercial opportunities, decide what to build, collaborate with product, engineering, and design teams, launch and improve products, and drive measurable business outcomes in a hands-on operating role.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and other financial services. Define product strategy, user problems, roadmaps, metrics, and launch plans; collaborate with engineering, design, data, compliance, operations, and business teams; simplify complex financial journeys; launch features; monitor performance; and drive continuous improvement through data, research, feedback, and experimentation.

Own product areas within AI Investing and other financial services, defining user problems, product direction, scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify complex financial products. Use research, feedback, experiments, metrics, and production insights to launch quickly, measure performance, and continuously improve customer experiences while balancing business impact, compliance, and operational complexity.

Own the end-to-end product direction and quality of AI-powered email capabilities. Define requirements, evaluation frameworks, quality standards, and measurable outcomes while balancing model quality, latency, cost, reliability, safety, and user experience. Partner closely with ML, backend, and client engineers on system design, experimentation, failure handling, and iteration. Drive prioritization, technical decisions, execution, and user trust in a fast-moving zero-to-one environment.

Own the end-to-end product strategy and execution for an AI-powered email application. Define AI behavior, system requirements, evaluation frameworks, quality standards, and user experiences while balancing reliability, latency, cost, safety, and usability. Partner closely with ML, backend, and client engineering teams to identify failure modes, improve system performance, prioritize work, and deliver predictable, trustworthy AI capabilities in a fast-moving zero-to-one environment.