Top Tech Jobs & Startup Jobs in Singapore

Own the end-to-end product direction and quality of an AI-native email application. Define AI behavior, system requirements, evaluation frameworks, quality standards, and user experiences while balancing quality, latency, cost, reliability, safety, and usability. Partner closely with ML, backend, and client engineering teams to identify failure modes, prioritize improvements, run experiments, and deliver predictable, trustworthy AI workflows.

Own product areas across AI stockbroking and financial services, defining user problems, product direction, scope, metrics, roadmaps, and launch plans. Partner with engineering, design, data, operations, compliance, and business teams to simplify complex financial products, ship features quickly, monitor performance, and iterate using data, feedback, research, and production insights. The role requires strong ownership, prioritization, communication, product judgment, and execution with limited guidance.

Own the end-to-end product direction for an AI-native email application. Define AI system and user experience requirements, translate model capabilities into product decisions, establish evaluation frameworks, and balance quality, latency, cost, safety, reliability, and usability. Partner closely with ML, backend, and client engineering teams to identify failure modes, improve AI behavior, prioritize roadmaps, and deliver trustworthy, predictable experiences in a fast-moving zero-to-one environment.

Own the end-to-end definition, evaluation, and quality of AI-powered email experiences. Translate model capabilities and technical constraints into product requirements, system decisions, priorities, and measurable outcomes. Partner with ML, backend, and client engineers to improve reliability, safety, latency, cost, usability, and trust. Identify failure modes, establish quality bars, drive experimentation, and guide execution in a fast-moving zero-to-one environment.

Own AI Investing product areas across financial services, defining user problems, product 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 make decisions, launch features, monitor performance, and drive continuous improvements while balancing user experience, business impact, compliance, and operational complexity.

Own the strategy, requirements, quality, and execution of an AI-native email application. Partner closely with ML, backend, and client engineers to define model and system behavior, evaluation frameworks, product trade-offs, and reliable user experiences. Drive prioritization, experimentation, failure-mode mitigation, and continuous iteration while balancing quality, latency, cost, safety, reliability, and user trust in a fast-moving zero-to-one environment.

Lead application engineering for an AI-powered email product across backend, mobile, and desktop platforms. Design reliable AI workflows involving orchestration, state, tool use, retries, fallbacks, and failure handling. Build APIs and abstractions connecting AI systems to product experiences, guide a senior engineering team, make architectural trade-offs, and establish strong observability, testing, monitoring, and operational foundations.

Own product areas for an AI-focused neobank across insurance, payments, savings, investing, travel, and other financial services. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify financial workflows; and use data, research, feedback, and production issues to drive continuous product improvement.

Lead application engineering for an AI-powered email product across backend, mobile, and desktop platforms. Design reliable AI workflow systems, APIs, orchestration, retries, fallbacks, and failure handling. Make architectural decisions, lead a small senior engineering team, mentor engineers, and establish strong observability, monitoring, testing, security, and operational practices. Partner with ML leadership to convert model capabilities into scalable, reliable product experiences while balancing latency, cost, reliability, and user experience.

Lead the engineering strategy and execution for an AI-powered email application across backend, mobile, and desktop platforms. Design reliable AI workflow systems, APIs, orchestration, retries, fallbacks, and failure handling. Lead a small senior engineering team through architecture, code reviews, mentorship, and technical decisions. Establish observability, monitoring, testing, and operational excellence while partnering with ML leadership to deliver scalable, reliable product experiences.