Senior Fullstack Software Engineer

Role Summary

This is a remote position.

You will be a founding-level senior engineer in a small, fast-moving team building our core platform from scratch. This is greenfield development — no legacy code to maintain, just high-impact work that shapes the product from day one.

We treat AI development tools (like Claude Code, Cursor, Copilot) as *core workflow engines*, not just helpers — you will use them daily to build features in days that would take others weeks.

You area greatfit if

You have 5+ years offullstackdevelopment experience and can take features fromideato production alone.

You love AI coding tools — you use them daily, know how to get the best out of them, and see them asgame-changers.

You build software for real people — you care deeply about making complex things simple, especially for non-technical users.

You move fast, but never compromise on safety, accuracy, or reliability — especially important in a regulated, safety-critical industry.

You are motivated by real-world impact: your code will prevent mistakes, protect people, and help businesses succeed.

You thrive in early-stage environments: you can handle ambiguity, define scope, prototype, and iterate quickly.

You are customer-obsessed, open-minded, and always learning.

Responsibilities

You will own the full stack

• Mobile-first, rugged user interfaces designed for technicians working in busy shop environments
• Backend systems that track results, flag missing steps, and automatically generate documentation, quotes, and invoices
• Everything in between: data models, business logic, integrations, and intelligence layers

What You Will Build

Core Platform Engine

A workflow system that guides technicians step-by-step through safety scans, system calibrations, and post-repair resets — drastically reducing errors, omissions, and compliance gaps.

AI-Powered Intelligence

Adaptive checklists and audit trails that adjust automatically based on vehicle make/model, repair type, and safety regulations — ensuring nothing is missed and everything is documented.

Revenue & Compliance Tools

Dashboards, alerts, and reports that help shop owners capture every billable service, reduce liability, and prove full compliance with industry standards.

Technician-First Interfaces

Simple, fast, and durable mobile/tablet UIs — built for real shop conditions: easy to read at a glance, hard to tap incorrectly, and fully usable even with dirty or gloved hands.

Integrations

Connect with existing tools: OEM diagnostic systems, repair management platforms, and vehicle data APIs — so our system fits seamlessly into how shops already work.

• Advanced AI Features:
• LLM-powered diagnostic summaries and natural-language documentation
• Automatic conversion of repair estimates into step-by-step work orders
• Intelligent automation that turns raw data into clear, actionable instructions

Requirements

Core Skills & Requirements

We look for deep experience and strong capability in

• System Architecture & Data Modeling: Designing scalable, maintainable, and secure systems.
• Security: Authentication, authorization, and data protection best practices.
• Frontend: React, TypeScript, modern UI patterns, and mobile-first responsive design.
• Backend: Node.js, Python, REST APIs, and service design.
• Data: PostgreSQL / SQL, database design, and performance optimization.
• Cloud Infrastructure: GCP, Azure, or AWS — deployment, scaling, anddevopsbasics
• AI Integration: Working with LLMs, AI tools, and intelligent features.
• DevOps: CI/CD pipelines, automation, and reliable delivery workflows.
• Ideal Candidate Profile

Nice-to-Have Qualifications

• Experience or familiarity with the automotive repair industry.
• Knowledge of OBD-II, ADAS systems, repair workflows, or shop management software.
• Experience building compliant software in regulated fields: automotive safety, healthcare, fintech, or insurance.
• Background in hardware, embedded systems, or vehicle data protocols (CAN bus, diagnostics APIs).
• Hands-on work with LLM pipelines : structured outputs, retrieval-augmented generation (RAG), or AI agent workflows.