Senior Fullstack Software Engineer
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Summary
Build a greenfield SaaS platform for auto-repair shops: full-stack React/TypeScript frontend, Node.js/Python backend, PostgreSQL, cloud devops, and LLM-powered workflows guiding technicians through safety scans and repairs.
This is a remote position.
Role Overview:
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 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.
6. 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
Requisitos
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, and devops basics
- AI Integration: Working with LLMs, AI tools, and intelligent features.
- DevOps: CI/CD pipelines, automation, and reliable delivery workflows.
Ideal Candidate Profile
You are a great fit if:
- You have 5+ years of fullstack development experience and can take features from idea to production alone.
- You love AI coding tools — you use them daily, know how to get the best out of them, and see them as game-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.
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.