VP of Engineering Applications, Artificial Intelligence (AI) Required, Work From Home

Next Step Systems•San Francisco, CA

3d•$225,000 - $275,000•Remote

About The Position

As the VP of Engineering Applications, you will turn intelligence into a real product. The VP of Engineering Applications is responsible for the engineering systems, teams, and execution that turn Machine Learning (ML) capability into reliable, fast, and intuitive user experiences across backend, mobile, and desktop platforms. The VP of Engineering Applications 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. This position is 100% Remote.

Requirements

Significant experience leading application or product engineering for complex systems.
Artificial Intelligence (AI) experience required.
Strong hands-on background building and shipping backend systems used in production.
Experience delivering Artificial Intelligence (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.

Responsibilities

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 Artificial Intelligence (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.