JPMorgan Chase & Co.

Software Engineer II- Java, AWS

JPMorgan Chase & Co. · Hyderabad, Telangana, India

Financial Services · 10,001+ employees

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

The software engineer will design, develop, and troubleshoot software components within an agile team to deliver secure and scalable technology products. They will also utilize enterprise-authorized AI tools to accelerate coding and documentation tasks while maintaining high security and quality standards.

What they look for

Java Spring AWS Kafka Event streaming Hibernate JPA SQL NoSQL System design Application development CI/CD Software development life cycle Technical troubleshooting Artificial intelligence Cloud technologies

Requirements

Candidates must have at least 2 years of applied experience and formal training in software engineering concepts. Proficiency in Java, Spring, AWS, Kafka, and database technologies is required, along with experience across the full software development life cycle.

Full description

You’re ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect software engineering opportunity for you.

As a Software Engineer II at JPMorganChase within the Consumer and Community Banking, you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.

Job responsibilities

  • Executes standard software solutions, design, development, and technical troubleshooting
  • Writes secure and high-quality code using the syntax of at least one programming language with limited guidance
  • Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications
  • Applies knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation
  • Applies technical troubleshooting to break down solutions and solve technical problems of basic complexity
  • Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development
  • Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems
  • Uses enterprise-authorized AI capabilities within the work environment to accelerate design comprehension and coding support (e.g., drafting unit tests and documentation), validating outputs and handling data according to sensitivity and security requirements.
  • Applies reuse-first, AI-assisted practices within SDLC/toolchain automation to reduce manual toil while maintaining security, resiliency, and traceability/auditability expectations.

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 2+ years applied experience
  • Hands-on experience in Java, Spring, AWS, Kafka, event streaming, Hibernate, JPA, SQL and NoSQL DB.
  • 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
  • Demonstrable ability to code in one or more languages
  • Experience across the whole Software Development Life Cycle
  • Exposure to agile methodologies such as CI/CD, Application Resiliency, and Security
  • Emerging knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
  • Working knowledge of using enterprise-authorized AI capabilities within the work environment to support software engineering workflows with strong validation habits and awareness of data sensitivity.
  • Ability to review and validate AI-assisted code and technical recommendations before use, escalating when uncertain and following security and data handling requirements.

Preferred qualifications, capabilities, and skills

  • Exposure to cloud technologies