Job description
In the existing App engineering system, responsible for the engineering integration and long-term maintenance of AI capabilities, including model invocation encapsulation, context building, result parsing, failure fallback, and experience convergence.
Design and implement reusable AI capability modules on the App side, supporting integration across multiple business scenarios (such as intelligent assistants, content generation, development assistance, problem analysis, etc.).
Responsible for the stability and performance governance of AI functions in complex client-side environments, including main thread safety, asynchronous scheduling, weak network handling, timeouts and retries, caching, and degradation strategies.
Incorporate AI capabilities into existing App engineering specifications, including:
- Code structure and dependency management
- Logging, monitoring, and problem localization
- Grayscale, rollback, and online risk control
Collaborate with AI backend, product, and platform teams to promote the evolution of AI functions from "experimental" to scalable and maintainable formal capabilities.
5 years or more of Android/iOS/Flutter/cross-platform App development experience, with a solid foundation in client-side engineering.
Experience in the long-term maintenance of complex functional modules, understanding the importance of scalability, stability, and technical debt control.
Familiar with the usage of large models in business and engineering boundaries, understanding the impact of prompts, context length, return uncertainty, and invocation costs on engineering design.
Familiar with AI coding tools such as Cursor, Claude Code, and Copilot.
Experience in the real-world implementation of AI capabilities on the App side (regardless of the scenario), able to explain:
- How to integrate
- What unstable or uncontrollable issues were encountered
- How they were ultimately resolved through engineering
Strong App performance optimization and problem localization skills, familiar with main thread governance, asynchronous models, memory, and resource management.
Proficient in at least one mainstream App development language (Kotlin/Swift/Dart, etc.), with good coding standards and engineering awareness.
Bonus points:
Experience in the design or implementation of AI-assisted development, AI code review, or AI analysis functions.
Experience in developing internal tool Apps, development efficiency tools, or platform-type modules.