Principal Software Engineer Manager

## About the role - Manage a team of high-performing individuals to deliver product, features with agility and quality. - Provide hands-on technical leadership: architecture, design, code reviews, development, quality assurance. - Lead by example to integrate AI first development in the team. - Partner with appropriate stakeholders to determine user requirements for a set of scenarios. - Drive identification of dependencies and the development of design documents for the platform. - Leads by example and mentor others to produce extensible and maintainable code used across products. - Leverages subject-matter expertise of cross-product features with appropriate stakeholders (e.g., program managers) to drive multiple group's project plans, release plans, and work items. - Proactively seeks new knowledge and adapts to new trends, technical solutions and shares knowledge with other engineers. ## Requirements - Bachelor'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 - Master'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 Bachelor's Degree in Computer Science or related technical field AND 15+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python - OR equivalent experience. - 6+ years people management experience. - Experience in large scale system architecture, design, development, testing, and release, including but not limited to web applications, microservices in layers, database design, API design, performance tuning, telemetry design and analysis. - Demonstrated programming skills and knowledge of architectural patterns for large, high-scale applications. - Proficient analytical skills with systematic and structured approaches to software design. - Deeper understanding of AI Models. - Committed collaboration and communication around articulating technical details.