Lead Software Engineer - Java, Spring, Kubernetes, Linux

JPMorgan Chase JPMorgan Chase · Banking · Mumbai, Maharashtra, India · Commercial & Investment Bank

Lead Software Engineer at JPMorgan Chase, focused on building and maintaining latency-sensitive trading systems for the Commercial & Investment Bank. The role involves leading a Java and React engineering team, owning the platform's technical vision, reliability, and scalability, and driving the adoption of AI-assisted engineering practices for code quality, delivery speed, and operational outcomes. Requires strong Java expertise, system design, leadership, and experience with SDLC, CI/CD, and security standards.

What you'd actually do

  1. Executes and oversees end-to-end software solutions, engineering standards, architecture, and technical troubleshooting for mission-critical trading systems.
  2. Writes secure, high-quality, and testable code in Java; collaborates on React APIs and backward-compatible rollout strategies.
  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. Designs and builds high-performance, latency-sensitive services with awareness of upstream/downstream systems and cross-asset use cases.

Skills

Required

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Hands-on experience in system design, application development, testing, and operational stability for mission-critical platforms.
  • Proven leadership of engineering teams and partnership with Product, Delivery/Program, and business stakeholders.
  • Expertise developing, debugging, and maintaining Java applications in large environments; strong API design.
  • Deep understanding of Java 17+ fundamentals, concurrency, memory management, and object-oriented design.
  • 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
  • Experience across the full Software Development Life Cycle; exposure to Agile methodologies, CI/CD, resiliency, and security.
  • Proficiency with Spring/Spring Boot, microservices, Kubernetes, Linux, and networking/messaging concepts.
  • Strong focus on automated testing; experience with TDD/BDD, unit testing, and modern CI/CD practices.
  • Effective communication with technical and non-technical audiences; ability to operate in globally distributed teams.

Nice to have

  • Familiarity with modern front-end technologies; experience collaborating with React teams.
  • Exposure to messaging systems and market protocols (e.g., MQ/Kafka; familiarity with FIX and Solace).
  • Experience with observability stacks and resilience engineering for low-latency trading platforms.
  • Familiarity with Python; awareness of investment banking, fintech, or financial markets

What the JD emphasized

  • mission-critical trading systems
  • latency-sensitive components
  • AI-assisted engineering practices
  • secure coding
  • responsible AI use