Software Engineer III - Full Stack

JPMorgan Chase JPMorgan Chase · Banking · Bengaluru, Karnataka, India · Corporate Sector

Software Engineer III (Full-stack) on the Infrastructure Platforms team at JPMorgan Chase. This role involves architecting, building, and optimizing software systems that support core internal services and tools. The engineer will design, implement, and evolve robust platform solutions, collaborate with cross-functional partners, and contribute to the technical direction and engineering standards. A key aspect is leveraging enterprise-authorized AI coding assist tools to improve code quality and delivery speed, while critically evaluating AI outputs.

What you'd actually do

  1. Design, develop, and deploy scalable full-stack platform tools for infrastructure teams.
  2. Enhance reliability and performance of critical internal systems through engineering best practices.
  3. Collaborate with engineering and operations groups to understand requirements and deliver solutions.
  4. Integrate new technologies and frameworks into platform services to improve developer productivity.
  5. Automate workflows and monitoring processes to streamline operations and reduce manual effort.

Skills

Required

  • Formal training or certification on software engineering concepts and 3+ years applied experience
  • Professional experience building full-stack applications for infrastructure or platform teams.
  • Proficiency in modern programming languages such as JavaScript/TypeScript, Python, Java, or Go.
  • Experience developing and deploying microservices and web applications using popular frameworks.
  • Strong grasp of database systems (SQL and NoSQL), RESTful APIs, and cloud infrastructure concepts.
  • Familiarity with CI/CD pipelines, DevOps practices, and automated testing methodologies.
  • Demonstrated ability to work cross-functionally on complex projects and deliver high-quality results.
  • 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.

Nice to have

  • Experience with container orchestration tools (Kubernetes, Docker) in production environments.
  • Knowledge of observability, monitoring, and logging solutions for large-scale systems.
  • Background in security compliance or distributed infrastructure design.
  • Contributions to open source or active participation in developer communities.

What the JD emphasized

  • enterprise-authorized AI coding assist tools
  • critically evaluate, validate, and refine AI-generated outputs
  • responsible AI use in engineering workflows