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Tier-1 brand, metro locations, and a visible engineering manager role increase candidate competition despite seniority.
Java, Azure, microservices and AI-native engineering skills are broadly transferable across industries.
Explicit 15–20 years, minimum leadership, and mandatory Java/Azure/AI-native expectations tighten screening.
Lead and grow an engineering team building enterprise-grade platforms using Java, .NET, and Azure with a focus on AI-native development practices.
Set and enforce AI-assisted development standards across the software development lifecycle including coding, testing, code review, and deployment.
Own end-to-end delivery of scalable enterprise applications balancing sprint quality, release velocity, and technical debt; make architectural decisions in collaboration with senior technical leaders.
15-20 years in software engineering with at least 3 years of team leadership experience; exceptional candidates with fewer years but stronger AI expertise considered.
Strong hands-on experience in Java development and solid Azure platform knowledge.
Demonstrated practical use and integration of AI coding tools (e.g., GitHub Copilot, Cursor) into team workflows.
Degree in Computer Science, Engineering, or equivalent.
Experienced engineering manager with operational and technical involvement in delivering software in agile, high-velocity environments.
Deep understanding and clear articulation of AI-native engineering practices and their application in real-world enterprise software development.
Comfortable making opinionated architectural decisions and influencing senior technical peers in a regulated or highly controlled industry environment (insurance, fintech, banking preferred but not mandatory).