Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Lead technical direction and hands-on execution for major software products and systems. Design scalable architectures across backend, frontend, APIs, databases, and infrastructure; write code; drive architecture decisions; solve production issues; improve testing, security, observability, and development practices; lead critical initiatives; and mentor engineers across distributed international teams.

Own product areas across AI investing and financial services, defining user problems, product direction, scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to ship customer-focused features. Use research, feedback, metrics, experiments, and production insights to improve products, balancing speed, usability, business impact, compliance, and operational complexity.

Own product areas for AI stockbroking and broader financial services, defining user problems, product direction, roadmaps, success metrics, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify financial products, ship features quickly, monitor performance, and iterate using data, research, feedback, and production issues.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and other financial services. Define user problems, product direction, scope, metrics, roadmaps, and launch plans. Partner with engineering, design, data, operations, compliance, and business teams to ship features, simplify financial workflows, monitor performance, and drive iterative improvements based on data, research, feedback, and production issues.

Owns technical direction and hands-on execution for major products and systems. Designs scalable backend, frontend, API, database, and infrastructure solutions; writes code; leads architecture decisions; resolves production issues; improves engineering quality; drives critical initiatives; and mentors engineers across teams.

Owns technical direction and hands-on execution for major products and systems. Designs scalable backend, frontend, API, database, and infrastructure solutions; writes code; drives architecture decisions; leads critical initiatives from design through production; improves engineering quality through testing, security, observability, and development practices; and mentors engineers across teams.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and other financial services. Define user problems, roadmaps, metrics, scopes, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial journeys; launch features; monitor performance; and drive iterative improvements using data, research, feedback, and production insights.

Build and maintain production-grade iOS applications using Swift and SwiftUI, integrating AI features through backend APIs. Design reliable AI interaction patterns, optimize performance, memory, battery, and latency, and support monitoring, feedback capture, and root-cause analysis. Collaborate with backend and ML engineers on API behavior, reliability, and user trust while shipping stable App Store experiences.

Own the strategy, requirements, evaluation, and execution of AI agent products and systems. Partner closely with ML, backend, and mobile engineers to make trade-offs across quality, latency, cost, reliability, and user experience. Define evaluation frameworks, drive prioritization, and ensure AI features are understandable, predictable, safe, and trusted. Translate model capabilities and feedback into product decisions and reliable real-world workflows.

Own the strategy, requirements, evaluation, and reliability of AI agent products. Partner closely with ML, backend, and mobile engineers to make trade-offs across quality, latency, cost, reliability, and user experience. Define offline and online evaluation frameworks, drive product execution, and ensure AI features are correct, predictable, safe, and trusted. Translate model capabilities and feedback into product decisions, roadmaps, and rapid iteration.