Software Engineer II - Java, Kafka, Microservices , Kubernetes
JPMorgan Chase & Co. (company site, opens in a new tab)2+ yrsMumbaiOn-siteDirect career pageEst. 18–28 LPA
Posted on 25 Sept
Reach people at JPMorgan Chase & Co.
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at JPMorgan Chase & Co. you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, develop, and maintain software components focusing on secure, stable, and highly scalable solutions within Corporate & Investment Bank technology products.
- Write high-quality, secure code primarily in Java, and troubleshoot technical issues considering upstream and downstream impacts.
- Leverage enterprise-authorized AI-assisted development tools to enhance code quality, delivery speed, and automation across the Software Development Life Cycle.
Minimum Requirements
- Formal training or certification in software engineering and at least 2 years of applied experience.
- Practical hands-on experience with Java, Multithreading, and Kafka.
- Experience in system design, application development, testing, and operational stability in a large corporate environment with modern programming and database querying languages.
- Experience using enterprise-authorized AI-assisted software development tools with demonstrated ability to critically evaluate AI-generated outputs.
Ideal Candidate Profile
- Experienced in full Software Development Life Cycle and agile methodologies including CI/CD, application resiliency, and security.
- Capable of delivering secure and scalable software solutions with an understanding of responsible AI use and data sensitivity in engineering workflows.
- Familiar with modern software engineering practices in a large corporate/financial environment and adept at leveraging AI-assisted automation tools effectively.