About
Worked for JP Morgan and Chase with payroll of Ascendion. Worked as Software Engineer with approx. 2 years of experience developing backend systems using Java and Spring Boot. Experienced in building REST APIs, microservices, and JMS-based asynchronous workflows for banking transaction processing. Skilled in Oracle SQL, MyBatis, and AWS, with experience in AI-powered chatbot integrations and core banking payment systems.
Skills & Expertise (36)
Work Experience
Software Engineer
Ascendion engineering private limited
Jun 2024 - Present
Developed backend services using Java and Spring Boot for a banking tax payment system and performed API testing and validation using Postman to ensure proper request handling and integration with upstream modules. Implemented JWT-based authentication and validation logic, including customer verification, duplicate request detection, cutoff-time checks, and holiday validations. Designed asynchronous communication using JMS-based messaging queues (MQ) to send payment requests to downstream banking systems for fund blocking and process responses received from them. Implemented background processing using multithreading to prepare and process transaction messages while maintaining system performance and reliability. Designed database sequence-based transaction reference generation, including both global and daily sequences to ensure unique transaction identifiers. Implemented scheduled batch jobs using AutoSys (.jil) and shell scripts (.sh) for end-of-day automation tasks. Implemented database operations using Oracle SQL and MyBatis for transaction persistence, query execution, and response handling from messaging queues. Participated in design discussions, code reviews, and production issue analysis, ensuring scalable and maintainable implementations. Collaborated with product managers, QA, and DevOps teams in an Agile/Scrum environment, utilizing Jira for sprint tracking and Git (Bitbucket) for version control and code management.
Client
JPMorgan Chase & Co.
Jun 2024 - Present
Developed backend services using Java and Spring Boot for a banking tax payment system and performed API testing and validation using Postman to ensure proper request handling and integration with upstream modules. Implemented JWT-based authentication and validation logic, including customer verification, duplicate request detection, cutoff-time checks, and holiday validations. Designed asynchronous communication using JMS-based messaging queues (MQ) to send payment requests to downstream banking systems for fund blocking and process responses received from them. Implemented background processing using multithreading to prepare and process transaction messages while maintaining system performance and reliability. Designed database sequence-based transaction reference generation, including both global and daily sequences to ensure unique transaction identifiers. Implemented scheduled batch jobs using AutoSys (.jil) and shell scripts (.sh) for end-of-day automation tasks. Implemented database operations using Oracle SQL and MyBatis for transaction persistence, query execution, and response handling from messaging queues. Participated in design discussions, code reviews, and production issue analysis, ensuring scalable and maintainable implementations. Collaborated with product managers, QA, and DevOps teams in an Agile/Scrum environment, utilizing Jira for sprint tracking and Git (Bitbucket) for version control and code management.
Client
Citi Bank
Jun 2024 - Present
Contributed to the development of an AI-powered banking chatbot that enables users to query financial information such as recent transactions, daily spending summaries, highest expenses, and spending patterns through natural language interactions. Integrated AI/LLM-based processing workflows within an agentic AI architecture to interpret user queries and generate contextual financial insights. Utilized AWS services including EC2 and S3 for deploying and hosting chatbot component and managing application storage. Implemented data aggregation and transaction insight logic using SQL, leveraging AWS RDS for storing and querying transaction datasets to support chatbot responses. Collaborated with AI engineers and backend developers in an Agile/Scrum environment, contributing to the development and integration of chatbot features for financial data insights.
Education
Bachelors of Engineering in Computer Science and Info Tech - Reva University
2020 - 2024 · India
Certifications
AWS certified cloud practitioner
Amazon Web service · 2025
AWS certificate
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Skills (36)
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