Qualifications

• Bachelor's or Master's degree in Software Engineering, Computer Science, Electrical Engineering, or related field.
• Extensive experience with distributed systems and cloud-native architecture including microservices and API-first design.
• Proficiency in core programming languages used in enterprise systems, particularly C++, C#, Java, Python, or Go.
• In-depth knowledge of Azure, focusing on security, networking, and platform services (preferred).
• Demonstrated success in deploying AI solutions in production environments with a focus on MLOps and governance.
• Strong skills in creating architecture documentation and driving standardization across teams.

Responsibilities

• Define and establish reference architectures, standards, and integration guardrails.
• Design cloud-native systems for scalability and modernization across product portfolios.
• Lead the production deployment of AI, focusing on model lifecycle and responsible integration.
• Collaborate with engineering and product leaders to identify impactful AI use cases.
• Influence and align diverse CTOs and engineering leaders on architecture and technical strategy.
• Set up architecture councils and best practices to facilitate technical decision-making.
• Sponsor innovative projects and measure their outcomes for scalability.

Benefits

• Flexible work environment with remote options.
• Professional development opportunities and training.
• Access to state-of-the-art tools and technology.
• Comprehensive health and wellness programs.