We are looking for a Full Stack AI Engineer who can move quickly in a startup environment and take ownership of building core product capabilities. This role requires someone who is comfortable across the entire stack, from frontend interfaces to backend systems, AI pipelines, and data architecture.
About Repair Ally
Repair Ally is building the next generation diagnostic copilot for automotive technicians. Modern vehicles contain 50+ control modules, hundreds of sensors, and millions of lines of software, making diagnosis increasingly complex. Repair Ally helps technicians and repair shops identify root causes faster through structured diagnostic workflows, technical knowledge retrieval, and AI-powered repair guidance. Our mission is to capture and scale the knowledge of the world’s best technicians so every technician can diagnose and repair vehicles with expert-level speed and accuracy. We are an early-stage startup building AI systems specifically designed for skilled labor and frontline workers, starting with automotive repair.
The Opportunity
The ideal candidate understands how to build production AI systems, not just call APIs. You should be comfortable working with LLMs, model training/fine-tuning, retrieval systems, and knowledge graphs. Because Repair Ally serves automotive technicians, familiarity with vehicle diagnostics, auto repair workflows, or automotive data systems is highly valuable.
What You’ll Do
AI Systems
- Build AI-driven diagnostic and repair guidance systems
- Train and fine-tune models on large automotive datasets
- Implement RAG pipelines integrating repair manuals, TSBs, and diagnostic procedures
- Design and maintain automotive knowledge graphs connecting symptoms, DTCs, components, and repair workflows
- Improve reasoning and diagnostic accuracy through evaluation and testing
Backend Systems
- Build APIs and services supporting AI-driven diagnostic workflows
- Design scalable data pipelines for ingesting automotive repair datasets
- Implement systems for structured diagnostic reports and repair instructions
- Integrate with external automotive data sources
Frontend & Product
- Build technician-friendly product interfaces
- Develop tools that translate complex diagnostics into clear workflows
- Optimize UX for technicians working in shop environments
Data Infrastructure
- Manage ingestion of large automotive datasets (repair manuals, DTC databases, service procedures)
- Structure data for AI training and retrieval
- Develop systems for ongoing model evaluation and improvement
Who We’re Looking For
You bring:
- 5+ years software engineering experience
- Experience building full stack applications (frontend + backend)
- Strong experience with AI/ML applications, including: LLM integration, Model training or fine-tuning, RAG systems, and Evaluation pipelines
- Experience designing knowledge graphs or graph databases
- Strong Python experience
- Experience with modern web stacks (TypeScript, React, Node, PostgreSQL, AWS)
- Experience working with production databases (Postgres, vector databases, graph databases)
Bonus points for:
- Experience working with automotive repair, diagnostics, or vehicle systems
- Familiarity with OBD-II, DTCs, vehicle sensors, or service procedures
- Experience with automotive data sources
- Experience building systems for technical knowledge retrieval
Why This Role
- Build AI systems that solve real-world problems for millions of skilled workers
- Work on hard technical problems in AI reasoning and diagnostics
- Help transform how knowledge is captured and shared in skilled labor
- Early employee with significant impact on company direction
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