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

Lead product security and incident response efforts: design and deploy security controls, hunt and investigate threats using endpoint/network/cloud telemetry, build detections and workflows, perform forensics, and partner with engineering to remediate vulnerabilities and improve secure design.

Lead strategy, roadmap, and delivery of AI/LLM-powered growth products across payments and financial operations. Own end-to-end product lifecycle, mentor product managers, build copilots/chatbots/recommendation systems, run experiments and analytics to drive PLG, and ensure responsible AI and regulatory compliance while launching products across regions and languages.

Lead strategy and roadmap for the corporate website to drive organic traffic, lead generation, and product sign-ups. Own hypothesis generation, A/B testing, experimentation, and analysis. Collaborate with Design, UX, Engineering, Marketing, RevOps, and Onboarding to optimize user flows, information architecture, and campaign effectiveness to deliver measurable commercial impact.

Manage global merchant credit risk by assessing prospective and existing merchants, defining KPIs and monitoring frameworks, building SOPs, creating reporting/dashboarding, partnering with Legal/Compliance/BD, and balancing growth with risk mitigation across payment channels.

Build and lead Airwallex's first-line commercial risk function, defining risk strategy and supportability frameworks, advising on complex deals, embedding commercial guardrails, designing portfolio monitoring and KPIs, leading incident post-mortems, and partnering cross-functionally to scale global coverage and train front-office teams.

Build and maintain user-friendly web interfaces for expense and procurement products using React and TypeScript. Implement micro frontend patterns, integrate with backend services via Apollo/GraphQL, collaborate with designers and PMs on shared UI components and design systems, participate in code reviews, triage bugs, and improve frontend engineering standards and observability.

Design, build, and deploy production AI agents and orchestration systems using tools like LangChain and LlamaIndex. Apply prompting, RAG, fine-tuning, and model selection. Architect agent reasoning and workflows, implement monitoring and evaluation, and integrate AI systems with backend and frontend services for scalable, reliable, compliant production deployments.

Design and implement scalable data models and ETL pipelines (batch and streaming), ensure data quality/SSOT, collaborate with product and platform teams to resolve issues, contribute to data governance, and explore practical integrations between data engineering and AI.

Design and operate scalable, event-driven backend systems in Python to power agentic AI workflows and real-time financial infrastructure. Own APIs, data architecture, reliability primitives, and platform foundations while partnering with ML and product teams to productionize AI-native financial systems.

Build and lead internal AI tooling and automation for security: develop threat-hunting and remediation tools, own large-scale log and ETL pipelines, maintain Kubernetes and serverless infrastructure, partner with product teams to reduce risk, and mentor junior engineers.