【研究發展處】Software Engineer

About the Role
We're looking for a hands-on Software Engineer to join our team, focused on building the tooling and data pipelines that keep our AI systems running reliably. You'll be deep in the stack — writing debugging utilities for live environments, investigating issues in the product we develop and the underlying telecom logic, developing data processing flows that feed our AI, and learning how complex Linux-based systems come together.

What You'll Do

• Develop and maintain internal tools for debugging and diagnostics in live production and staging environments
• Investigate and troubleshoot issues in our product and telecom logic, working closely with field, support, and engineering teams to root-cause problems in live systems
• Build and maintain data processing pipelines that power our AI workflows
• Write automation scripts in Python to streamline data ingestion, transformation, and delivery
• Work with SQL and databases to support data quality, accessibility, and performance
• Contribute to performance-sensitive components and low-level utilities in C++
• Collaborate with cross-functional teams to resolve data, product, and integration issues and improve system reliability

What We're Looking For

• Experience in a software, data, or systems engineering role
• Familiarity with Linux — comfortable in the terminal and willing to learn process management, networking, and filesystems
• Proficiency in Python for scripting, automation, and tooling
• Working knowledge of SQL for querying and manipulating data
• Exposure to C++ for performance-sensitive or low-level work
• Comfortable working in live environments and eager to triage issues with guidance
• Strong debugging instincts — you enjoy digging into a problem until you find the root cause
• Interest in investigating product behavior and telecom protocols/logic in real-world deployments

Nice to Have

• Familiarity with telecom systems, protocols, or field application engineering
• Familiarity with relational or non-relational databases (e.g. PostgreSQL, MySQL, MongoDB)
• Exposure to data pipeline or workflow tools (e.g. Airflow, Spark, Kafka)
• Experience with Docker and containerized environments
• Familiarity with CI/CD pipelines (e.g. GitHub Actions, Jenkins, GitLab CI)
• Familiarity with gdb, strace, or similar debugging tools
• Any prior exposure to AI/ML data workflows

What You'll Bring
A practical, no-nonsense engineering mindset. You're comfortable in the terminal, curious about how things break — whether in the data pipeline, the product, or the telecom logic underneath — and motivated by making data flow reliably and teams move faster.