Qualifications

• Bachelor's or Master's in Software Engineering, Computer Science, Electrical Engineering, or a related field.
• Strong experience with distributed systems and cloud-native architecture (microservices, event-driven design).
• Hands-on proficiency in core languages like C++, C#, Java, Python, and Go; C++ is especially relevant here.
• Deep expertise in Azure, focusing on security, networking, identity, and platform services.
• Proven track record in production AI deployment, including MLOps and governance.
• Strong architecture documentation skills with the ability to enforce standards across teams.

Responsibilities

• Define reference architectures and technical standards for APIs, data, integration, and reliability.
• Design scalable cloud-native systems and create modernization roadmaps.
• Lead architecture for production AI deployment, ensuring responsible integration and governance.
• Align multiple CTOs and senior engineering leaders with differing strategies.
• Establish architecture councils and technical steering forums to facilitate decision-making.
• Propose and oversee pilots/POCs, measuring outcomes for scalability across the organization.

Benefits

• Work in a pivotal leadership role affecting company-wide architecture decisions.
• Opportunity to drive innovation and modernize existing software solutions.
• Collaboration with senior leaders across various engineering teams.
• Ability to shape the company’s AI strategy and its integration into systems.