Head of Engineering

Company

Tread is the AI-native operating system for the $660B construction materials logistics market: the aggregate, asphalt, and concrete behind every road, bridge, and building in the country. Our customers run the gamut: enterprise producers and contractors that supply the world's largest infrastructure projects, alongside the family-owned hauling fleets that have moved the material this work depends on for generations. They're the operators who actually build the roads, bridges, and buildings around us. Most of the work still happens on paper tickets, phone calls, and disconnected scale houses. We're building the software they run on.

We crossed $1Bn in monthly delivered load value on the platform in March 2026. We’re at ~$XM ARR, and growing fast. Our enterprise customers reconcile real money, real freight, and real P&L against our data every day. Tread is the most important software they use.

We’re a Series A company backed by Mucker Capital.

We’re in growth mode. If you are fulfilled by ownership and a life-changing outcome, let’s connect.

Role

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.

The successful candidate will already have experience operating an AI-first engineering organization where coding agents are responsible for a significant portion of production software delivery. They should be able to describe:

• how work flows from specification through implementation using agents

• how architecture, code quality, and correctness are reviewed

• how evaluation frameworks prevent regressions and hallucinations

• how AI integrates into CI/CD and release management

• where human judgment remains essential

We are not looking for someone who is simply enthusiastic about AI. We're looking for someone who already operates an AI-native engineering organization and can install that operating system at Tread.

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.

In this role, you will:

• 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).

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.

Why Tread

• We’re building the software for the operators who build America. Construction materials logistics is essential infrastructure for an essential industry, and the incumbents are decades behind.

• You’ll earn meaningful Series A equity in a business that has been substantially de-risked. We have product-market fit, paying enterprise customers, and a $1Bn+/month volume signal.

• We have clarity on what we need to do to win. We are in growth mode, not testing the waters.

• Our customers are bought in, and we are working with some of the largest haulers, producers, and contractors in the country.

• We’ve proven we can build better software than what’s in market, and we win consistently against our competitors.

• We are an AI-native engineering org from top to bottom. Our SDLC is built around coding agents, and continuing to invest in it is core to the Head’s job, not a side project.

• We are building for an enduring industry that has to exist. Roads, bridges, buildings, and the materials that go into them are not going anywhere, regardless of what changes with technology or investor sentiment.

• You will work directly with the CEO, the VP of Customer Operations, the SVP of Revenue, and our Engineering team. No layers between you and impact.

• We pay competitive salaries and offer real benefits: medical, dental, vision, 401(k), unlimited PTO, and a transportation stipend.

Why You Shouldn’t Work With Us

• You are not excited to work in-person.

• You cannot put in the hard work to build a $B business.

• You are not excited to design and operate an AI-native engineering system hands-on (agents, SDLC workflows, evals, CI/CD integration).

• You view AI as an assistant rather than a fundamental change in how engineering organizations should operate.

• You don’t ship high-quality code, fast.

Technology

Current stack: Ruby on Rails, GraphQL, React, TypeScript, Flutter, PostgreSQL, AWS.

AI tooling is part of the infrastructure: a shared skills library across Claude Code and Cursor, namespaced agent skills for diff review and PR feedback, devcontainers, fast feedback loops, pre-approved permissions, and cloud agent support. We deploy multiple times per week, review PRs the same day, and invest in testing and correctness up front so on-call stays light. Improving the SDLC is first-class engineering work.

Interview Process

• Recruiter conversation

• Meeting with the CEO

• Meeting with the Engineering team

• Technical systems design and AI engineering case study focused on transforming an engineering organization using AI-native development practices.

• Board Member

• Reference conversations

• Offer