AI Application Developer / AI 應用開發工程師 (Full-Stack & Engineering Focus)

Job Title: AI Application Developer (Full-Stack & Engineering Focus)

Job Highlights

Enjoy extreme technical autonomy and core decision-making authority.

Base salary + lucrative project profit-sharing; AI-assisted coding strongly encouraged.

About the Role

This position seeks a core engineering expert with exceptional end-to-end delivery capabilities to spearhead the engineering and commercial deployment of cutting-edge AI technologies. We empower our core developers with absolute technical autonomy and a highly competitive incentive structure (base salary + project profit-sharing). We champion an agile development culture and strongly encourage the deep integration of AI coding assistants to achieve maximum efficiency in building 0-to-1 SaaS architectures.

Key Responsibilities

• 0-to-1 MVP Development: Independently lead the end-to-end development of novel AI applications (e.g., RAG-based knowledge bases or multi-step Agent tools), handling everything from backend logic to frontend UI prototyping and rapid iteration.
• Core Architecture & AI Optimization: Possess absolute technical authority, independently driving core business logic design, Prompt Engineering, model fine-tuning, and resolving technical bottlenecks.
• System Engineering & Deployment: Transform AI applications into robust SaaS products. Take charge of system architecture design, database construction, API encapsulation, and cloud deployment to ensure high-quality project delivery.
• AI-Empowered Coding: Masterfully utilize AI coding assistants (e.g., Cursor/Copilot) to rapidly generate business code. Demonstrate exceptional code review and logic optimization skills to ensure the security and stability of the AI system.

Requirements

Must-Haves

• End-to-end Production System Ownership: 2+ years of experience as a technical lead for core systems throughout their full lifecycle. Proven track record of independently driving architecture design, deployment, on-call monitoring, and incident resolution.
• Deep Code Review & Refactoring Expertise: Proficient in at least one mainstream backend language (e.g., Python) with exceptional ability to read across unfamiliar codebases. Able to pinpoint logical correctness, security vulnerabilities, and maintainability risks—going far beyond mere code style corrections.
• Database & Complex Authorization Architecture: Solid foundational judgment in designing robust schemas, optimizing indexes, and formulating smooth data migration plans. Able to precisely define and implement "who can access what" authorization and data isolation models (e.g., RBAC/ABAC).
• Technical Influence & Mentorship: Substantial experience in code review and technical leadership. Able to provide constructive, actionable review feedback that genuinely elevates the engineering judgment of the collaborative team.

Nice-to-Haves

• Cutting-Edge AI Implementation & Measurement: Practical experience developing LLM applications (e.g., RAG, Agents) along with a strong grasp of system Eval (model evaluation) and output quality measurement methodologies.
• Cloud Native & IaC: Hands-on experience with AWS / GCP / Azure platforms; proficient in containerization technologies (Docker / Kubernetes) or familiar with Infrastructure as Code tools (Terraform / Pulumi).
• Application Security: Familiar with the OWASP Top 10 defense framework, with practical experience in Threat Modeling and secure code reviews.
• High-Concurrency Operations: Experience in architecture design and low-level performance tuning for high-traffic, high-concurrency systems.
• 0-to-1 System/Team Building: Proven track record of building complex system architectures from scratch or successfully assembling a technical team.