JPMorgan Chase & Co.

Software Engineer III - Java, Spring boot, Public cloud

JPMorgan Chase & Co. · Hyderabad, Telangana, India

Financial Services · 10,001+ employees

7 h ago Closes in 2d
Mid (2-5 yrs) Full-time India
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About the role

Design and deliver secure, scalable technology products as a seasoned member of an agile team. Execute software solutions, develop production code, and leverage AI coding tools to improve delivery speed and quality.

What they look for

Java Spring Boot Public Cloud AWS GCP Azure Microservices RESTful API Kafka Spark Docker Kubernetes Helm System Design NoSQL AI-assisted Development

Requirements

Requires 3+ years of experience in software engineering with proficiency in Java, Spring Boot, and cloud technologies. Candidates must have hands-on experience with distributed systems, microservices, and AI-assisted development tools.

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 the Consumer and Community Banking, 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
  • 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
  • Contributes to software engineering communities of practice and events that explore new and emerging technologies
  • 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.

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 3+ years applied experience
  • Hands-on practical experience in system design, application development, testing, and operational stability
  • Proficient in coding in one or more languages
  • Experience with distributed systems and cloud technologies (AWS, GCP, Azure, etc.)
  • Experience with micro services/RESTful API, relational/NoSQL databases, data modeling and data ingestion frameworks
  • Hands-on experience with data streaming and messaging frameworks (Kafka, Spark, etc.)
  • Understanding of dependency injection frameworks (Spring / Spring Boot, etc.)
  • Understanding of containers (Dockers, Kubernetes, Helm, etc.)
  • 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.

Preferred qualifications, capabilities, and skills

  • Cloud Certification
  • Practical cloud native experience
  • In-depth knowledge of the financial services industry and their IT systems