Work with engineers, product managers, and partner teams to deliver experiences with the right overall design and architecture, leveraging AI where it can meaningfully improve deployment efficiency, reliability, and customer outcomes. Provide mentorship and coaching to engineers both in, and beyond, your team, including the adoption of modern AI-powered development practices and tools. Own and deliver complete features across the development lifecycle, including design, architecture, implementation, testability, debugging, shipping, and servicing. Drive innovation through automation and AI-powered solutions to improve deployment intelligence, operational efficiency, and service reliability at hyperscale. Ensure your team delivers clean, well-thought-out code with an emphasis on quality, performance, simplicity, durability, scalability, maintainability, and effective use of AI-assisted engineering practices. Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Proficiency in AI-native development — working within Agent Harnesses (GitHub Copilot CLI, Coding Agents), authoring Markdown specs/ADRs and YAML configs as Agent-consumable inputs, orchestrating multi-step Agentic workflows across the SDLC, and reviewing Agent-generated code and PRs with production-grade rigor. Fundamentals in data structures, algorithms, object-oriented design, and scalable systems. Experience building, testing, debugging, and maintaining production-quality software, following established engineering practices as well as leveraging large language models (LLMs). Problem-solving and technical judgment skills, with the ability to design scoped solutions, debug complex issues, and improve service performance. Experience with cloud platforms and distributed/service-oriented architecture. Experience with reliability, monitoring, and performance optimization practices. Experience in driving AI (LLM/ML) based engineering solution.
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