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Tier-1 brand, metro location, mid-career leadership band, and broad technical leadership increase competition.
Core backend and cloud skills are transferable, but payments and responsible-AI governance increase domain specificity.
Explicit 5+ years, 2+ leadership years, and mandatory Java/Kafka/cloud/AI governance requirements raise filter strictness.
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Provide leadership, technical coaching, and oversight to multiple entry-level to mid-level software engineering teams focused on financial technologies within Payments Technology.
Own tactical operations, resource allocation, budget influence, and execution of engineering processes that integrate AI-assisted development and SDLC automation to improve delivery speed and quality.
Set and measure operating practices for AI-assisted engineering across teams, ensuring security, resiliency, and reuse of technology assets while enabling cross-team and stakeholder collaboration.
5+ years applied software engineering experience plus 2+ years leading technologists on complex technical problems within domain expertise.
Proficiency in Java 8+, Multi-threading, Spring Boot, Kafka, ActiveMQ, RESTful HTTP, Oracle/MySQL.
Experience leading team adoption of AI-assisted development tools including governance, quality controls, and secure handling of data.
Practical cloud-native experience with AWS/Private Cloud, Docker/Kubernetes; formal background in Computer Science, Engineering, Mathematics or related field.
Experienced in managing and coaching multiple software teams with a focus on complex technical decision-making and operational efficiency in financial services technology.
Skilled in integrating enterprise AI-assisted engineering tools into SDLC processes and driving measurable improvements in delivery throughput and software quality.
Strong influence and advisory capability at leadership level regarding technical strategy, budget, and responsible AI use within engineering workflows including security and resiliency.