Key Responsibilities
Technical Ownership Thru Application Lifecycle
- The Lead Software Engineer is responsible for design build deployment and maintenance of tailor-made and/or software packages or the adaptation of existing ones.
- Provides day-to-day application support: Possess good initiative be able to actively follow up on online issues and do a good job of sustaining as daily duty.
- Complex malfunctions incidents and bugs are managed understoodanalyzed reported and solved.
- Continuous study analyze and manage the code scripts and other assets and ensure compatibility with overall product and architecture strategy.
Key player in solution implementation
- The business needs are analyzed and converted into functional and/or technical specifications
- Act as key player in solution implementation deliver the core modules and handle complex technical challenges including model selection deployment options context engineering Retrieval-Augmented Generation (RAG) AI agents etc
- Major changes to existing applications are implemented. Technical support by diagnosing and solving complex incidents is guaranteed. Complex technical questions are answered.
Technical Quality & Excellence
- Ensuring the non-functional system qualities: stability scalability performance security and consistency.
- Ensure code quality (Readability Maintainability Efficiency Reliability Testability) by defining and cascading developer guidance proceeding code review.
- Adopt quality gate automation test or other quality related standard in CI/CD pipeline.
Technology Leadership & Innovation
- Stay up to date with cutting-edge technologies particularly in adopting AI into technical solutions & development.
- Experiment with new frameworks architectures and methodologies
- Promote engineering AI best practices within the team to improve development efficiency and code quality.
- Bachelors or above degree in computer science or related field.
- 5 years of experience in software engineering including hands-on experience in AI-related or data-intensive applications.
- Speak and write in both English and Chinese.
- Proven track record of delivering end-to-end production-grade AI system solutions.
Technical Skill
- Solid in Python coding with Sophisticated in adopting principles: (modular design DRY testability).
- Practical knowledge in AI-oriented development frameworks such as LangChain LangGraph or similar orchestration tools.
- Good knowledge & practical experience in Elasticsearch Redis Kafka Kubernetes CI/CD Postgresql/Mysql cloud-based hosting monitoring and alerting.
- Analytical Skills: Strong analytical and problem-solving abilities with a proven track record of tackling complex technical challenges.
- Familiarity with major foundation models (e.g. GPT Qwen) and ability to evaluate AI component suitability is a plus.
Soft Skills & Behavioral Traits
Curiosity & Fast Learning: A strong desire to learn and rapidly apply new technologies and methodologies.
Innovative Thinking: Creativity in proposing technical solutions to complex business problems and thinking outside the box.
Communication Skills: sufficient ability of active listening and translating complex technical concepts into clear business-friendly language for stakeholders.
Problem-solving mindset with a focus on delivering practical technical solutions that drive real business outcomes.
Intrinsic motivation to contribute to customer value and company success with willingness to take responsibilities beyond the role and assigned tasks.
Experience with AI-assisted programming tools (e.g. Cursor GitHub Copilot Codeium) and ability to leverage them effectively to improve development productivity and code quality.
Required Experience:
Staff IC
Pionnier de la science des matériaux depuis plus de 130 ans, Michelin construit un manufacturier leader mondial des composites et expériences qui transforment notre quotidien.