苹果SW Development Engineer: System RF Data Ecosystem
任职要求
Minimum Qualifications Master's degree in Computer Science, Engineering, or a related field, with 4+ years building production-quality full-stack applications. High proficiency in Python, including REST API development, Flask-based web applications, and production-ready code. Hands-on experience with modern front-end frameworks (e.g., React) and relational databases such as PostgreSQL, including schema design and query optimization. Proven ability to diagnose and resolve issues across the full stack, including development and production environments. Familiarity with cloud environments (AWS, GCP, Azure), CI/CD workflows, version control, and modern software engineering best practices. Strong familiarity with Generative AI principles and demonstrated proficiency using AI coding agents (Claude Code, Gemini CLI, or equivalent) as an active part of the development workflow — including prompt engineering, context management, and iterative code generation. Understanding of how AI assistan…
工作职责
Build Full-Stack Systems: Design, implement, and maintain end-to-end applications spanning front-end interfaces, backend services, and APIs in distributed cloud environments. Develop AI-Enabled Tools and Platforms: Build and deploy LLM-integrated applications, agentic workflows, and data analysis tools that surface actionable engineering insights. Design and implement skills, plugins, and MCP server integrations that extend AI assistants with access to internal data sources, APIs, and engineering systems. Deliver Scalable, Production-Ready Software: Develop reliable, performant services, applying performance best practices to ensure efficient, high-volume workflows. Apply Software Fundamentals and Testing: Write clean, maintainable, well-tested code and participate in code reviews to ensure high-quality software. Debug Across the Stack: Diagnose and resolve issues across front-end, backend, and infrastructure using logs, metrics, and systematic problem-solving. Contribute to Cloud & DevOps Workflows: Participate in CI/CD pipelines, cloud deployments, monitoring, and operational best practices for system reliability. Collaborate and Communicate: Work closely with senior engineers and cross-functional teams to clarify requirements, make technical decisions, and deliver impactful solutions.
Build Full-Stack Systems: Design, implement, and maintain end-to-end applications spanning front-end interfaces, backend services, and APIs in distributed cloud environments. Develop AI-Enabled Tools and Platforms: Build and deploy LLM-integrated applications, agentic workflows, and data analysis tools that surface actionable engineering insights. Design and implement skills, plugins, and MCP server integrations that extend AI assistants with access to internal data sources, APIs, and engineering systems. Deliver Scalable, Production-Ready Software: Develop reliable, performant services, applying performance best practices to ensure efficient, high-volume workflows. Apply Software Fundamentals and Testing: Write clean, maintainable, well-tested code and participate in code reviews to ensure high-quality software. Debug Across the Stack: Diagnose and resolve issues across front-end, backend, and infrastructure using logs, metrics, and systematic problem-solving. Contribute to Cloud & DevOps Workflows: Participate in CI/CD pipelines, cloud deployments, monitoring, and operational best practices for system reliability. Collaborate and Communicate: Work closely with senior engineers and cross-functional teams to clarify requirements, make technical decisions, and deliver impactful solutions.