Backend Engineer

Software Engineer - Backend

San Francisco

Engineering

In office

Full-time

Transform How Frontline Work Runs

Enterprises struggle to manage hundreds of millions of dollars in frontline labor spend due to decades-old software and manual processes, creating massive, avoidable costs. Frontline labor often represents 40% of the P&L, yet the systems managing this $3 trillion market were built for static schedules and limited flexibility.

ReadyOn was founded to reject that paradigm. Staffing is not a scheduling problem; it is a real-time supply–demand orchestration problem. ReadyOn is an AI-native labor operating system, built from the ground up for AI agents to perform real-time labor optimization - much like ridesharing platforms that match drivers and riders in real time, but applied to frontline labor instead of fixed, one-size-fits-all schedules.

Who's Building It

AI is not a bolt-on feature in our platform. Every decision, from demand forecasting to shift assignment, flows through an adaptive, autonomous decision layer that learns from operational data and continuously optimizes for cost, compliance, and worker satisfaction. Behind that system is a founding team of experts in labor markets, enterprise software, and AI-enabled platforms:

• Reza – Engineering leader who scaled enterprise systems at Google, Yahoo, and AT&T

• Dominic – Operator who optimized labor-intensive operations in 21 countries

• Mohammad – Stanford professor and leading expert in algorithmic market design

ReadyOn has already proven product–market fit with multiple multi-million-dollar customers, consistent expansion within existing accounts, and measurable ROI that moves stock prices.

Hands-On Builders Leading AI Innovation

ReadyOn is searching for senior engineers who love to code and ship impactful products. The core enterprise system is live; now the work is about sharpening, extending, and scaling real-time labor insights across thousands of sites and users. As an engineer here, you’re not layering AI onto the edges of a legacy tool, you’re building the core decision layer that orchestrates how thousands of shifts, locations, and workers come together every day.

Our engineers roll up their sleeves across core engineering, AI, and platform teams to get things built. You’ll find TypeScript and Python everywhere, powering everything from core services to user-facing features. This is a place for people who launch, learn, and continuously make systems smarter in production.

You’ll Thrive in This Role If You

• Have 5+ years of backend engineering experience working with production systems.

• Dive into ambiguity, excel in hands-on, high-impact environments, and drive solutions without waiting for perfect specs.

• Care about clean system design, scalability, and architectural elegance and aren’t afraid to rethink the usual approaches.

• Enjoy close collaboration with product, design, and AI research teams to deliver new experiences customers use.

• Focus on business outcomes, not just technical output, and love finding solutions to real problems.

• Are fluent in TypeScript and NestJS (or other Node.js frameworks) and know how to design decoupled services and robust enterprise interfaces; GraphQL experience is a major plus.

• Bring deep expertise in PostgreSQL: schema design, query optimization, migration management, and handling concurrency in large-scale environments.

• (Bonus) Have hands-on experience with conflict resolution in collaborative systems, graph processing, feature stores, or real-time coordination tools.

• If you’re looking for predictability and structure, this probably isn’t the place for you - we thrive in fast-changing, flexible environments driven by initiative, not routine.

This Might Not Be the Right Role If You

• Prefer clear-cut structure, established processes, or state-of-the-art internal operating systems; we embrace rapid change and flexibility.

• Want a traditional corporate setting with standard roles, well-defined career ladders, and steady routines.

• Rely on top-down guidance, detailed documentation, or formal onboarding; autonomy and self-direction are critical here.

• Crave predictability or highly specialized functions; we reward outcome-driven effort, learning, and the ability to flex between roles rather than sticking to rigid paths.