Software Engineer III - Java Backend, Kafka, AWS, DevOps
JPMorgan Chase & Co. Bengaluru, Karnataka, India
Financial Services · 10,001+ employees
About the role
Design and deliver secure, scalable technology products as a member of an agile team within the Fraud Risk department. Execute software solutions, perform technical troubleshooting, and leverage AI-assisted tools to improve code quality and delivery speed.
What they look for
Requirements
Requires 3+ years of applied experience in software engineering with hands-on expertise in Java, Spring, Kafka, and database systems. Candidates must have experience in system design, DevOps practices, and the ability to validate AI-generated code outputs.
Full description
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorganChase within Consumer & Community Banking Fraud Risk Team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- 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.
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience.
- Hands-on experience building enterprise grade backend systems using Java, Spring, Kafka and DBMS (RDBMS or NoSQL) and experience in system design, application development, testing, and operational stability
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- 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.
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Experience with latest DevOps practices and tools
Preferred qualifications, capabilities, and skills
- Exposure to cloud platforms(AWS) & familiarity with Kafka
- Experience with deploying and managing containerized microservices in AWS
- Experience setting up active system monitoring, centralized logging, and alert configurations using Prometheus, Grafana, Dynatrace, or Datadog.
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