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Tier-1 brand, mid-level generalist title, and metro location increase applicant competition.
Strong engineering skills transfer, but payments domain and enterprise AI governance reduce portability.
Requires 5+ years, formal training, AI/tooling experience, and security/governance expectations causing moderate filtering.
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Own the embedding of architecture standards and AI-assisted development practices within 10,000 Payments engineers through hands-on involvement including coding, coaching, and conducting gemba walks.
Drive adoption of enterprise-authorized AI-assisted engineering tools to improve code quality, delivery speed, and operational outcomes, establishing consistent validation standards.
Lead knowledge sharing via presentations and educational content to propagate best practices, identify anti-patterns, and connect effective solutions across multiple teams.
5+ years applied experience with formal training or certification in software engineering concepts.
Hands-on experience in system design, application development, testing, and operational stability.
Proven track record of influencing engineering practices beyond immediate team and leading AI-assisted software development tool adoption.
Strong written and verbal communication skills including experience creating technical content.
Experienced technical lead or influencer in large corporate environments with multi-team collaboration.
Practitioner of hands-on software engineering who also serves as an educator or mentor through presentations, blogs, or training.
Expertise in responsible AI use within engineering workflows including secure, compliant adoption and coaching engineers on these practices.