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Tier-1 brand, popular backend role, mid-level experience band, and metro location increase applicant competition.
Backend engineering skills transferable broadly, though banking domain knowledge is desirable but not strictly required.
Explicit 5+ years, Python backend, AWS knowledge, and responsible AI governance expectations enforce strict filters.
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Develop high-quality backend Python code adhering to software engineering best practices like SOLID, YAGNI, and KISS.
Lead adoption and governance of AI-assisted engineering tools for code quality, delivery efficiency, testing, and operational metrics.
Own product lifecycle from development to maintenance, support other teams in issue resolution and promote product adoption across teams.
5+ years of applied software engineering experience with formal training or certification.
Strong experience in object-oriented programming and test-driven development using Python.
Proven experience leading enterprise use of AI-assisted software development tools with knowledge of secure and responsible AI practices.
Experience with distributed computing architectures and event-based architecture; knowledge of AWS.
Experienced in building scalable backend systems within financial or complex technical environments, preferably with trade or investment banking context.
Capable of leading cross-functional agile teams with a focus on integrating AI-assisted development workflows.
Demonstrates technical leadership in software lifecycle, quality standards, and operational problem solving in a global team setting.