Backend & DataOps engineer building and operating cloud-native services, with a focus on applying AI to solve practical problems. Specialized in AI model integration, REST APIs, MongoDB, Kafka, and reliable service operations.
Primary Focus
Building and operating cloud-native services while applying AI to real-world engineering problems.
System Snapshot
A compact view of the way I work: service-minded, cloud-native, and focused on applying AI where it creates practical value.
$ whoami
> Tiyao Li
$ cat focus.txt
> cloud-native services
> backend engineering + data operations
> practical AI integration
$ cat stack.txt
> python, fastapi, mongodb, kafka
> docker, kubernetes, azure, ci/cd
> pytorch, codex, copilot, claude_code
$ echo $STATUS
> building reliable services with AI in the loop
The Journey
A progression from sensor data recording into cloud-native services for AI-assisted auto-labeling.
Bosch - Cloud-native Auto-labeling Services & Data Operations
Building and operating a cloud-native auto-labeling platform for perception data, supporting use cases such as Near Field Model, Occupancy, and Blockage.
Bosch - Sensor Data Recording & Measurement Automation
Worked on Messtechnik and sensor data recording for ADAS truck radar projects, supporting Mercedes-Benz and Volvo truck platforms.
Technical Stack
Primary Strength
Building Python backend services for auto-labeling workflows, with clean REST APIs, async processing, database integration, and maintainable service boundaries.
Production Context
Connecting perception data, backend service logic, AI model outputs, and label delivery for multiple automated labeling use cases.
Infrastructure
Containerized services deployed and operated in cloud-native environments, supported by CI/CD and operational discipline.
Data Services
Working with persistent service state and event-driven flows for reliable backend processing and operational visibility.
AI / Machine Learning
Integrating AI model behavior into backend services for labeling workflows, with a practical focus on inference outputs rather than model training.
Modern Engineering Workflow
At work, using GitHub Copilot as the approved AI coding assistant for code understanding, implementation support, and day-to-day engineering productivity. For personal projects and everyday problem solving, exploring tools such as OpenCode, Codex, and Claude Code while keeping compliance, privacy, and human ownership in focus.
Academic Foundation
A foundation in electrical engineering, information technology, and international engineering study.
Master of Science (M.Sc.)
Electrical Engineering and Information Technology
Master's Thesis
Deep learning for 3D MRI image quality assessment, comparing SVM-based methods with a fully convolutional neural network implemented with Keras and TensorFlow.
Bachelor of Science (B.S.)
Electrical Engineering and Information Technology
Bachelor's Thesis
Power electronics and control systems, including MATLAB/Simulink simulation, harmonic analysis, PID controller configuration, and control strategy optimization.
Exchange Semester
Electrical Engineering and Information Technology
International Experience
Completed an exchange semester in Hong Kong, broadening academic perspective through an international engineering environment.
In my professional work, I use GitHub Copilot as the approved AI coding assistant to support code understanding, implementation, refactoring, and day-to-day development within the boundaries of company policy.
Outside of work, I actively experiment with OpenCode, Codex, and Claude Code for personal projects and everyday problem solving. I treat these tools as practical thinking partners while keeping compliance, privacy, architecture, reliability, and data quality under human control.
"Meta-note: This portfolio site was created through a human-AI collaboration between Tiyao Li, Google Stitch, and Codex."
Connect
Especially interested in backend engineering, DataOps, cloud-native services, AI integration, service operations, and production data workflows.