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Tier-1 brand, popular backend lead title, mid-level experience, and Bangalore location increase applicant competition.
Requires financial-services domain knowledge and compliant AI engineering experience, reducing cross-industry transferability.
Explicit 5+ years and mandatory Java, AWS, AI/LLM implementation and secure engineering requirements make filters strict.
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Provide technical leadership and guidance for software engineering teams developing secure, scalable technology products.
Lead adoption and implementation of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
Drive product design and technical decisions across multiple business functions, ensuring adherence to secure coding and automation standards.
5+ years of applied software engineering experience with formal training or certification.
Advanced proficiency in Java 17+ including Spring, Hibernate, JMS, Spring Boot, Spring MVC.
Experience with AI-assisted software development tools and responsible AI use in engineering workflows.
Strong experience with AWS cloud technologies and relational (Oracle) or NoSQL databases.
Experienced in leading technical teams and influencing engineering practices at a function-wide level within complex agile environments.
Deep understanding of integrating AI-assisted tools in the software development lifecycle with focus on security, compliance, and operational resiliency.
Background in financial services IT systems and applying cloud and AI technologies to business use cases, including hands-on implementation of Agentic AI or LLM solutions.