施耐德Senior Principle Software Architect
任职要求
Qualifications - External Bachelor’s / master's degree in engineering 8+ years of experience on software design, development, and project management Deep understanding of latest edge computing technical architecture and technology trends Strong experience with hands-on skills in .NET core and Java technologies Solid knowledge of product security / cyber security with hands-on experience in security requirements, thread modeling, secure software architecture & design, and secure software implementation Competent experience in systems management inclu…
工作职责
Description - External Co-work with and thus support software development teams Leads software product architecture design, involves in product detailed design and review, covers the whole software life cycle, based on Schneider Electric product platforms and market requirements to enhance edge systems portfolio Act as key developer and owner of highly reusable and exceptionally reliable fundamental software components Work with project teams to provide software consultations to customers and other stakeholders
In this role, you will be managing a team of experienced deep learning performance architects to analyze deep learning networks and push the evolution of our deep learning computing system in hardware/software co-design approach. You will establish team objectives to meet schedules and goals, establish and evolve policies and procedures that affect the immediate organization, communicate with senior management for team vision and development. You’ll collaborate with members of the deep learning software framework teams and the hardware architecture teams to accelerate the next generation of deep learning computing system. The scope of your team's efforts includes deep learning workloads characterization, performance tuning and analysis, optimizing the present generation of our software tech stack and drive the evolution of the next generation of deep learning hardware and software architecture, and other general engineering management work.
• Design, develop, and maintain new features while enhancing existing systems for performance, scalability, and reliability. • Write clean, testable, and maintainable code that adheres to design specifications, coding patterns, and security best practices. • Conduct timely code reviews to ensure quality, coach peers, and drive adherence to standards, diagnosability, and maintainability. • Troubleshoot live-site issues, deploy fixes, and implement solutions that reduce incident volume and improve system observability. • Collaborate with cross-functional teams to align on architecture, dependencies, and project goals, resolving blockers and driving success. • Ensure security compliance by configuring, updating, and maintaining tools, applying secure design principles, and validating security invariants. • Incorporate user feedback and telemetry data into design decisions, continuously improving product value, accessibility, and user experience.
• Design, develop, and improve scalable infrastructure to support the next generation of AI applications, including copilots and agentic tools. • Drive improvements in architecture, performance, and reliability, enabling teams to bring to bear LLMs and advanced agent frameworks at scale. • Collaborate across hardware, software, and research teams, mentoring and supporting peers while encouraging best engineering practices and a culture of technical excellence. • Stay informed of the latest advancements in AI infrastructure and contribute to continuous innovation across the organization.