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Tier-1 brand, popular backend title, metro location, and broad cloud skillset drive high candidate competition.
Requires deep financial services domain knowledge and banking systems experience, reducing cross-industry transferability.
Explicit 8+ years, mandatory backend, cloud, and specific tech stack and financial domain increase shortlisting rigidity.
Lead design, development, and debugging of secure, scalable fraud protection software solutions within Payments Trust and Safety Technology.
Optimize application and infrastructure performance, using automated tools and setting benchmarks to ensure scalability across diverse environments.
Drive adoption of AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, while influencing cross-functional leaders and teams.
Minimum 8 years of software engineering experience with formal training or certification.
Proven expertise in advanced Python, Java, Spring Boot, AWS (Glue, ECS/EKS, Lambda, S3, EC2, Kafka, NLB), Aurora Postgres, Terraform, and databases.
Experience leading AI-assisted development tools correctly integrating secure, responsible AI workflows.
Strong understanding of financial services IT systems and full SDLC with agile methodologies including CI/CD and security practices.
Experienced in leading performance optimization and automation in high-scale financial technology environments.
Demonstrates practical expertise in using AI tools like GitHub Copilot to improve engineering productivity and code quality with secure validation standards.
Familiar with enterprise architecture, unified user experience design, and cross-team case management workflows within financial services contexts.