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

Own the strategy, roadmap, contracts, and success metrics for Felix’s payments orchestration platform. Define workflow interfaces, reliability guarantees, retries, compensation, observability, and self-service tooling. Lead platform migration and expansion to additional products while balancing remittance reliability with infrastructure investment. Partner with engineering, operations, compliance, and finance, and guide architecture decisions. The role requires strong distributed-systems knowledge, payments or transaction-processing experience, excellent writing, data fluency, and platform product-management experience.

Own the strategy, roadmap, contracts, reliability, and adoption of Felix’s payments orchestration platform. Define workflow primitives, interfaces, retry and compensation semantics, observability, SLAs, and self-service tooling. Lead platform evolution from remittances toward multiple financial products while balancing reliability and investment. Partner with engineering, operations, compliance, and finance, using data to measure workflow success, completion time, manual intervention, and integration speed.

Own the strategy, roadmap, contracts, reliability, and adoption of Felix’s payments orchestration platform. Define workflow primitives, interfaces, retry and compensation semantics, observability, SLAs, and self-service tooling. Lead platform evolution to support multiple financial products while balancing remittance reliability and infrastructure investment. Partner with engineering, operations, compliance, and finance, using metrics and data to improve workflow success, completion time, intervention rates, and integration speed.

Own the strategy, roadmap, contracts, and success metrics for Felix’s payments orchestration platform. Define reusable workflow primitives, reliability guarantees, APIs, observability, onboarding, and migration plans that enable multiple financial products. Partner with engineering, operations, compliance, and finance on architecture and platform adoption. The role requires strong distributed-systems knowledge, payments experience, technical communication, data fluency, and the judgment to prioritize platform investments over stakeholder demands.

Leads AI initiatives from concept through deployment, adoption, and ownership. Translates priorities into technical plans, coordinates dependencies across engineering and product teams, drives decisions, manages risks, defines evaluations, and ensures deployment readiness. Establishes support and monitoring ownership, partners with security and governance teams, and converts project learnings into reusable delivery standards.

Lead AI initiatives from concept through deployment and adoption. Translate priorities into technical plans, coordinate dependencies across engineering and business teams, drive decisions, manage risks, oversee evaluations and deployment readiness, establish support ownership, and ensure solutions deliver measurable outcomes. The role also requires hands-on technical fluency with Python, SQL, APIs, LLM SDKs, data pipelines, agent systems, and evaluation practices.

Leads AI initiatives from concept through deployment, adoption, and ownership. Responsibilities include creating technical plans, coordinating dependencies across engineering and business teams, driving technical decisions, managing risks and blockers, coordinating evaluations and deployment readiness, establishing support and monitoring ownership, and ensuring AI governance reviews. The role requires hands-on technical fluency, LLM and agent evaluation knowledge, operational rigor, and strong cross-functional communication.

Build and debug LLM agents, integrations, and AI workflows using Python and APIs. Provide technical office hours, mentoring, code reviews, and debugging support to colleagues. Develop reusable agent frameworks, starter kits, evaluations, documentation, and learning resources. Partner with internal teams on AI platform adoption, identify skill gaps, track learning outcomes, and escalate complex data, security, or production issues.

Build and debug LLM agents, integrations, and AI workflows using Python and APIs. Provide technical office hours, mentoring, code reviews, and debugging support; develop reusable agent frameworks, starter kits, evaluations, documentation, and learning resources. Partner with internal teams to identify skill gaps, deliver hands-on training, troubleshoot AI issues, and escalate complex data, security, and production problems while promoting safe, maintainable AI adoption.

Build and debug LLM agents, integrations, and AI workflows using Python, APIs, and LLM SDKs. Provide technical office hours, mentor colleagues, troubleshoot prompts and tool calls, develop reusable starter kits and documentation, and lead hands-on AI training. Partner with internal teams on escalations, data safeguards, evaluations, and platform improvements while helping employees independently adopt and maintain AI solutions.