Head of Engineering

Tread•San Francisco, CA

11d•$200,000 - $260,000•Onsite

About The Position

We’re looking for a hands-on engineering leader who can help define and operate the next generation of our AI-native engineering system, partnering directly with the CEO to evolve how software is built at Tread. You will partner directly with the CEO on building the category-defining operating system for construction materials logistics. The team you lead today is under 10 engineers shipping at aggressive velocity. We're investing heavily in an AI-driven SDLC — which you will help drive — with the product specs, architecture documentation, code review, and quality gates in place to make ~100% AI-generated code work. We've operated this way since March 2026. Tread is also a financial system of record. We move freight, we move money, and our customers reconcile their business against our platform. Correctness, reliability, and trust are non-negotiable.

Requirements

7-12 years building software, with demonstrated engineering leadership in high-growth startups (Seed–Series B/C) or founder experience.
Background in hypergrowth startups. Ideally Seed through Series C, or founder experience.
Fluent and opinionated about AI-native engineering. You've personally built or operated production engineering workflows where AI agents participate throughout the software lifecycle, including specification, implementation, testing, code review, evaluation, deployment, and maintenance.
Strong engineering judgment around speed vs. correctness. You know where to intentionally optimize for rapid iteration, where correctness is non-negotiable, and how to build systems that recover safely when things fail.
Experience operating payments or financial systems at scale.
Deep technical credibility. Comfortable discussing architecture, distributed systems, AI infrastructure, evaluation systems, developer tooling, and modern software delivery practices at every level of the organization.
Lives in modern AI tooling every day. Claude Code, Cursor, coding agents, prompt engineering, context management, evaluation workflows, and multi-agent collaboration are part of your daily engineering practice—not technologies you've merely experimented with.
Hiring instincts at the senior and staff level. You can identify, calibrate, and close engineers who are stronger than you in their domain.
Engineers who’ve worked with you choose to work with you again, and we’ll talk to them.
Eager to work in-person at our San Francisco office 3-5 days/week.

Responsibilities

Own engineering execution across product engineering, platform, data, payments, AI infrastructure, internal developer tooling, and the AI-native software development lifecycle.
Recruit top-tier talent and raise our bar for excellence. Push the team to strike the balance between speed and a reliable product. Have the hard conversations early.
Drive the AI-native SDLC forward. Personally invest in the shared skills library, namespaced agent review pipelines, devcontainers, CI, and cloud agent infrastructure that lets a small team operate at scale.
Design and continuously improve evaluation systems for AI-generated software, including quality gates, benchmark suites, regression testing, rollout strategy, rollback procedures, and model performance monitoring.
Set technical direction across the Rails API, data layer, payments business logic, and clients.
Make build-vs-buy and platform-investment calls that balance speed with long-term leverage.
Own platform reliability and trust posture: uptime, data integrity, payment accuracy, security, and incident response.
Partner closely with the CEO on the product roadmap and serve as a key thought partner. The roadmap includes deepening AI agents into customer workflows and embedding fintech throughout the app (instant funding, ACH for B2B payments, financing).