We are looking for an experienced software engineer to lead the development of our distributed edge compute platform. This role demands a deep understanding of hyperscalers like AWS, Azure, or GCP, and the ability to design and operate large-scale systems. The successful candidate will contribute to the platform's architecture, ensuring fault tolerance, consistency, and efficient traffic routing.

• Extensive experience (5+ years) with hyperscaler technologies (AWS, Azure, GCP) and managed services.

• Have worked at or intimately with AWS, Azure, GCP, or similar-scale platforms - built internal cloud, compute, or infrastructure services

• Proven track record in designing and operating large-scale distributed systems.
• Strong fundamentals in distributed systems, including consistency models and fault tolerance.
• Proficiency in API design and development, with an understanding of versioning and SDK foundations.
• Experience with Kubernetes and containerization technologies for resource management.
• Solid understanding of high-throughput traffic routing and network protocols.
• Ability to work independently and manage complex technical tasks.
• Excellent communication and collaboration skills, with a willingness to share knowledge.
• Familiarity with security best practices and data privacy regulations.
• Master's degree in Computer Science, Engineering, or a related field. PhD preferred.

• Design and implement a massively distributed edge compute platform, ensuring high availability and fault tolerance.
• Develop external-facing APIs, considering design, versioning, and interactions with customers and partners.
• Optimize high-throughput L7 traffic routing for efficient data processing.
• Utilize Kubernetes internals for resource management and container deployment.
• Collaborate with a team of engineers to build and operate the platform, sharing knowledge and best practices.
• Translate distributed systems complexity into clear architectural tradeoffs
• Communicate infrastructure risks and mitigation strategies to executive stakeholders
• Manage technical requirements from customers’ needs.
• Collaborate effectively with AI/ML systems engineers, Hardware architects, Network engineering teams, Security and compliance teams
• Present scalability models and reliability metrics in measurable, defensible terms
• Mentor engineering teams on distributed systems best practices
• Anticipate internal and external business challenges and / or regulatory issues and drive process, product or service improvements that create competitive advantage.
• Stay updated with the latest trends and technologies in distributed systems and edge computing.
• Establish design reviews and architectural governance standards
• Ensure the platform's security and data privacy, adhering to industry standards and regulations.
• Conduct code reviews and provide constructive feedback to maintain code quality.