Lead Software Engineer - Java Aws

JPMorgan Chase JPMorgan Chase · Banking · Hyderabad, Telangana, India · Consumer & Community Banking

Lead Software Engineer role at JPMorgan Chase focused on designing and delivering technology products within the Trust & Security Identity team. The role involves executing software solutions, developing secure code, and driving team adoption of enterprise-authorized AI-assisted engineering practices. It also includes leading evaluation sessions for external vendors and driving communities of practice for new technologies. Requires formal training/certification in software engineering with 5+ years of experience, proficiency in Java AWS, Microservices, SpringBoot, Kafka, CassandraDB, CockroachDB, Terraform, and cloud-native experience. Emphasizes demonstrated experience with AI-assisted development tools and understanding of responsible AI use.

What you'd actually do

  1. Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
  2. Develops secure high-quality production code, and reviews and debugs code written by others
  3. Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  4. 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.
  5. Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

Skills

Required

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Advanced in one Java AWS, Microservices SpringBoot
  • Kafka, CassandraDB, CockroachDB, Terraform, cloud native experience
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
  • Proficiency in automation and continuous delivery methods
  • Proficient in all aspects of the Software Development Life Cycle
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)

Nice to have

  • Familiarity with modern front-end technologies
  • Exposure to cloud technologies
  • Experience with application development on AWS

What the JD emphasized

  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices