Software Engineer III

JPMorganChase · Bengaluru · 3+ yrs experience · Posted 2026-07-28

Tech stack: AWS, Jenkins, Kafka, Kubernetes, PostgreSQL, Terraform

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About the role

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. Join a team that delivers high-impact risk technology while embracing AI-assisted ways of working.
Job summary
As a Software Engineer III at JPMorganChase within our Consumer & Community Banking
Responsibilities:
- Execute software solutions, including design, development, and technical troubleshooting, thinking beyond routine approaches to solve complex problems
- Create secure, high-quality production code and maintain algorithms that run synchronously with appropriate systems
- Produce architecture and design artifacts for complex applications and ensure design constraints are met through implementation
- Gather, analyze, and synthesize large, diverse data sets to develop visualizations and reporting that drive continuous improvement
- Proactively identify hidden problems and patterns in data and use insights to improve coding hygiene and system architecture
- Leverage AI-assisted development practices and tools to improve developer productivity and delivery outcomes
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Qualifications:
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Hands-on experience in system design, application development, testing, debugging, and operational stability in a large corporate environment
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
- Proficiency building and supporting application programming interfaces (APIs), including REST APIs, Swagger/OpenAPI documentation, and messaging/streaming with Kafka
- Hands-on experience with automated testing and quality practices, including JUnit, Mockito, SonarQube, and code coverage tools
- Experience with cloud and infrastructure technologies including Amazon Web Services (AWS) services (ECS, RDS, Lambda, Step Functions), Kubernetes, Terraform, and relational databases (Oracle and PostgreSQL)
- Experience using integrated development environments and validation/diagnostic tooling including IntelliJ IDEA, VS Code, Postman or Bruno, and observability/monitoring tools such as Splunk, Grafana, and the ELK stack
- Solid understanding of the software development life cycle and agile delivery practices, including continuous integration/continuous delivery (CI/CD), application resiliency, and security using Jenkins, Spinnaker, or equivalent tools, plus strong collaboration skills (requirements detailing and providing estimates for epics)
- Hands-on experience using AI developer tools such as Copilot and Claude and delivering in an “AI first” development environment
- Experience building solutions using agentic AI frameworks
- Experience with contract testing and behavior-driven development (BDD) approaches such as Cucumber/Gherkin
- Experience with test automation frameworks such as Karate

Qualifications

- Formal training or certification on software engineering concepts and 3+ years applied experience
- Hands-on experience in system design, application development, testing, debugging, and operational stability in a large corporate environment
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
- Proficiency building and supporting application programming interfaces (APIs), including REST APIs, Swagger/OpenAPI documentation, and messaging/streaming with Kafka
- Hands-on experience with automated testing and quality practices, including JUnit, Mockito, SonarQube, and code coverage tools
- Experience with cloud and infrastructure technologies including Amazon Web Services (AWS) services (ECS, RDS, Lambda, Step Functions), Kubernetes, Terraform, and relational databases (Oracle and PostgreSQL)
- Experience using integrated development environments and validation/diagnostic tooling including IntelliJ IDEA, VS Code, Postman or Bruno, and observability/monitoring tools such as Splunk, Grafana, and the ELK stack
- Solid understanding of the software development life cycle and agile delivery practices, including continuous integration/continuous delivery (CI/CD), application resiliency, and security using Jenkins, Spinnaker, or equivalent tools, plus strong collaboration skills (requirements detailing and providing estimates for epics)
- Hands-on experience using AI developer tools such as Copilot and Claude and delivering in an “AI first” development environment
- Experience building solutions using agentic AI frameworks
- Experience with contract testing and behavior-driven development (BDD) approaches such as Cucumber/Gherkin
- Experience with test automation frameworks such as Karate

Responsibilities

- Execute software solutions, including design, development, and technical troubleshooting, thinking beyond routine approaches to solve complex problems
- Create secure, high-quality production code and maintain algorithms that run synchronously with appropriate systems
- Produce architecture and design artifacts for complex applications and ensure design constraints are met through implementation Gather
- analyze, and synthesize large, diverse data sets to develop visualizations and reporting that drive continuous improvement
- Proactively identify hidden problems and patterns in data and use insights to improve coding hygiene and system architecture
- Leverage AI-assisted development practices and tools to improve developer productivity and delivery outcomes
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

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