Software Engineer (AI-Native)

AI-Driven Software Platform For Automotive Service Industry

We are building an AI-driven software platform for the automotive service industry, and we are hiring our founding builder. This is a strictly in-office role. It is not remote. It is not hybrid. We want someone close to the business, the workflows, the CTO, and the real problems — because we believe the hardest problems get solved fastest face to face. If you can only work remotely, this isn't the fit.

The role is not what it sounds like. We don't care where you went to school — or whether you went at all. We want someone who taught themselves to write code because they couldn't not, and who developed a real strategy for building software along the way, not just the ability to follow a tutorial. Anyone from the car world will get the distinction. Plenty of dealership techs can pull a trouble code, run the factory test plan, and swap the part it names. Far fewer can put a scope on a problem the test plan doesn't cover and fix the car that had everyone else stumped. One follows a procedure; the other has a diagnostic strategy and can work outside their comfort zone. We want the second kind, pointed at software. In practice that means you can code, you use AI tools aggressively to move fast, and — the part that actually matters — you can break a messy problem into precise steps, direct the AI to build it, and judge whether what came back is right. Typing code is the easy part now. The thinking is the job. If you love building software and have the horsepower to think deeply and learn fast, but no company has given you a real shot because your résumé lacks the pedigree — this is the shot. The person we're describing tends to lock onto a hard problem and not let go: they'll disappear into it, chip away at it for hours or days, and come back with it solved. If that's how your mind works, you'll fit here.

We are building a closed-loop operating system for automotive repair businesses — where every workflow connects to the next one. Shop management, estimates, repair orders, invoices, customer and vehicle history, accounts payable, credit-card and bank transactions, document reconciliation, accounting, payroll, technician pay, owner dashboards, and AI-assisted automation throughout. A repair order should connect to an invoice. An invoice should connect to accounting. A vendor bill should connect to a payment. A credit-card charge should connect to a document. A payroll decision should connect to the work actually performed. Every important action should be traceable. Every exception should be reviewable. Every workflow should make the system smarter over time. This is a money-movement platform — accounting and payroll have to be right, not just look right. Which is exactly why we need someone who thinks in verification, edge cases, and audit trails, not someone who trusts whatever the AI hands back.

Modern software development has changed, and we've changed with it. You will use AI coding agents and LLMs aggressively. We do not care whether every line was typed manually. We care about results, clean architecture, documentation, and maintainability. Our expectations are simple:

• Use AI aggressively, and verify everything it produces
• Keep the architecture clean and the data models sound
• Document decisions — use markdown files, architecture notes, and implementation plans to preserve project knowledge
• Design audit trails so important decisions can be traced later
• Decide where automation is safe and where a human must approve
• Don't blindly trust generated code; don't dismiss it either
• Leave the system better organized than you found it

You'll work directly with ownership and technical leadership. No layers of management, no committees, no endless meetings. Some days you'll map a workflow on a whiteboard. Some days you'll write instructions for the AI and review what it built. Some days you'll realize the original idea was wrong and help design a better one. That's normal here.

This is not a startup guessing at an industry from the outside. Our founder has spent over four decades in the automotive repair business and owns repair shops across multiple states. He has already founded software now used by independent shops and major national chains. We understand the repair workflow, the accounting problems, and where existing shop-management systems fall short. Now we're building the next platform with AI-assisted development and real operating experience behind it.

The platform's backend is built in Go, with Python for AI, OCR, and document processing, React on the front end, and PostgreSQL for data. You don't need to know Go on day one — if you've taught yourself other languages, you'll pick it up fast, and you'll lean on AI to move quickly. What's not optional is the judgment to read what the AI writes, reason about it, and know whether the system is doing the right thing.

You may be a strong fit if you:

• Taught yourself to code and built your own way of working — no CS degree required, and none expected
• Reach for a new tool or approach when the standard playbook runs out, instead of stopping at the edge of the procedure
• Think in systems and processes, and like understanding how things really work
• Can break a vague, messy problem into clear, precise, buildable steps
• Already build real things with AI tools and have internalized the spec-and-verify loop
• Notice the details and edge cases other people miss
• Care about clean data, permissions, and audit trails
• Prefer clear, direct communication and deep focus over constant meetings, and tend to lock onto a problem until it's solved
• Are comfortable saying "this doesn't make sense" when something is wrong
• Want meaningful responsibility early and would rather solve a real problem than chase trends

Backgrounds that often map well: QA/test, implementation or solutions work, automation, business/systems analysis, technical product work — or a sharp, self-taught builder who's become genuinely fluent with AI tools. Domain experience in automotive or accounting is a real plus. This is probably not for you if you need every task fully defined before starting, prefer meetings to building, want a large team and a highly structured corporate environment, think AI output should be trusted without review, dislike documenting your work, or are only looking for remote work.

Base salary starts at $85,000, with meaningful equity included. We're an early-stage startup, so we'll be direct: this is not a big-company package. The upside is in joining early, owning real problems, and helping build something valuable. We're open to structuring cash and equity to the person — more cash with less equity, or more upside with more startup risk. Benefits: health insurance with low deductibles, plus dental and vision; 401(k) with company match; paid vacation and paid holidays.

No cover letter. No generic AI-generated application. Your resume matters less than proof you can think and build. Send us:

1. Your GitHub, live demos, or anything that shows what you've built (screenshots, docs, automations, and workflows all count)
2. The most important thing you personally built or owned — what problem it solved and why you approached it the way you did
3. Which AI coding tools you use, and how you verify their output before trusting it
4. How you use documentation, markdown, or architecture notes to organize a project
5. One time you disagreed with the original product or technical direction, and what you did about it

If you built something useful that other people never fully appreciated, start there. We're not looking for the best interviewer. We're looking for the right builder.