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About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
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As a Lead Software Engineer within the Asset & Wealth Management Alternatives Team, you will join an agile team to build and modernize platforms supporting alternative investments. You will serve as a hands-on Java/Spring Boot developer responsible for re-platforming critical applications from on-premises environments to AWS while delivering cloud-native services with high engineering discipline. Your daily work involves designing distributed integration patterns using messaging and event streaming technologies like Kafka, AWS MSK, SQS, SNS, or Kinesis to improve system resiliency and observability. You will also lead the adoption of enterprise-authorized AI-assisted development tools for code review, refactoring, and testing while ensuring security and performance standards. The role requires expertise in Java, Spring Boot, and cloud-native architecture to solve complex technical challenges within the financial services and alternative investments domain.
Develop and modernize production-grade Java and Spring Boot applications for alternative investment platforms.
Re-platform critical legacy applications from on-premises environments to AWS cloud-native infrastructure.
Design and implement distributed integration patterns using messaging and event streaming services like Kafka or SQS.
Lead the adoption of enterprise-authorized AI tools to accelerate coding, testing, and incident analysis.
Establish validation standards for AI-generated code to ensure security, performance, and accuracy.
Provide technical guidance and direction to internal teams, contractors, and external vendors.
Perform code reviews and debug production code to ensure high quality and operational stability.
Advocate for firmwide engineering frameworks and tools within the broader software development lifecycle.
What we're looking for
Formal training or certification on software engineering concepts and 5+ years of applied experience.
Proven hands-on experience in system design, application development, testing, and operational stability in production environments.
Advanced proficiency in Java for enterprise backend development with practical experience using Spring Boot or equivalent frameworks.
Hands-on experience designing and operating integrations using messaging and event streaming services like Kafka, AWS MSK, SQS/SNS, or Kinesis.
Practical hands-on cloud-native experience building and deploying services on the AWS platform.
Demonstrated experience leading the use of enterprise-authorized AI-assisted development tools while ensuring output correctness, performance, and security.
Strong understanding of responsible AI usage in engineering workflows, including data sensitivity and secure handling of inputs/outputs.