VP Engineering
San Francisco, CA
Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior.
Turn intelligence into a real product. You are responsible for the engineering systems, teams, and execution that turn ML capability into reliable, fast, and intuitive user experiences across backend, mobile, and desktop platforms.
This role is a senior engineering leader who stays close to the product, makes hard technical decisions, and holds a high bar for quality and delivery.
Own the application engineering strategy and execution across backend, mobile, and desktop.
Lead and grow a small, senior applications team, including backend, mobile, and desktop engineers.
Set the architectural direction for AI-powered product workflows, APIs, and client integrations.
Ensure AI capabilities are integrated into the product with clear abstractions, predictable behavior, and graceful failure modes.
Partner closely with Machine Learning leadership to translate model capability into shippable product features.
Make high-impact decisions across latency, cost, reliability, security, and user experience.
Establish clear ownership boundaries across backend, mobile, and desktop to prevent architectural drift.
Ensure production readiness: observability, monitoring, retries, fallbacks, privacy, and cost controls.
Balance speed and discipline – shipping quickly without compromising long-term system quality.
Significant experience leading application or product engineering for complex systems.
Strong hands-on background building and shipping backend systems used in production.
Experience delivering AI-powered products, with a deep understanding of model integration trade-offs.
Excellent system design skills across services, APIs, clients, and data flows.
Comfort operating across platforms (backend, mobile, desktop), even if your depth is in one.
Proven ability to make high-impact technical decisions under ambiguity.
A strong bias toward shipping, iteration, and learning from real-world usage.
Low ego, strong judgment, and the ability to raise the technical bar for the entire applications organization.
Reliable, low-latency AI user experiences across backend, mobile, and desktop
Clear architectural boundaries that allow teams to move fast without constant rewrites.
Measurable improvements in system performance, stability, and production reliability.
Strong observability and operational discipline across all application systems.
A small, senior team that ships frequently, owns what they build, and raises the technical bar.
Team members are empowered, growing in their roles, and able to make high-impact contributions.
June 29, 2026