JPMorgan Chase & Co.

Software Engineer III - Java, AWS, Kafka

JPMorgan Chase & Co. · Hyderabad, Telangana, India

Financial Services · 10,001+ employees

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

Design, develop, and maintain secure and scalable backend services and APIs using Java, Spring Boot, and AWS. Collaborate with stakeholders and leverage AI coding tools to improve code quality and delivery speed.

What they look for

Java Spring Boot AWS Kafka AWS Lambda ECS Fargate System Design API Development CI/CD Agile Methodologies AI-Assisted Development Postgres DB SQS S3 SNS Event Bridge

Requirements

Requires 3+ years of software engineering experience with mandatory proficiency in Java, Spring Boot, AWS, and Kafka. Candidates must have hands-on experience in system design, operational stability, and the use of 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 the ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
  • Design, develop, and maintain backend services and APIs using Java and Spring Boot on AWS.
  • Develop and deploy serverless applications using AWS Lambda , ECS Fargate.
  • Focus on code hygiene and system architecture , write production ready code.
  • Engage with stakeholders, including product owners, leads, and architects, as needed and in a timely manner.
  • 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 of applied experience.
  • Proficiency in Java, Spring boot and AWS and Kafka is mandatory for this role.
  • Experience with AWS services (Not limited), including ECS, SQS , S3, SNS , AWS Postgres DB, Event bridge and Lambdas.
  • Hands-on practical experience in system design, application development, testing, and operational stability.
  • Experience in developing, debugging, and maintaining code in an enterprise with one or m
  • Hands-on practical 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
  • Overall knowledge of the Software Development Life Cycle. Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, 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

  • Familiarity with modern front-end technologies