Senior Manager of Software Engineering - Java, Kafka

JPMorgan Chase JPMorgan Chase · Banking · Bengaluru, Karnataka, India · Commercial & Investment Bank

Senior Manager of Software Engineering for Payments Technology at JPMorgan Chase, focusing on leading and coaching multiple technical teams. The role involves setting and scaling operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation, applying knowledge of AI-assisted development tools to drive efficiency, and ensuring collaboration and issue mitigation. Requires strong understanding of responsible AI use in engineering workflows and experience leading multi-team adoption of AI-assisted development and delivery tools.

What you'd actually do

  1. Provide overall direction, oversight, and coaching for a team of entry-level to mid-level software engineers that work on basic to moderately complex tasks
  2. Be accountable for decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures
  3. Sets and scales operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across multiple teams to improve delivery speed, quality, and operational outcomes; establishes measurable expectations (e.g., throughput, defect reduction, reliability) and ensures consistent validation, security, resiliency, and reuse of proven patterns.
  4. Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive efficiency and support capacity unlock initiatives across teams, prioritizing reuse of existing firm technology assets.
  5. Ensures successful collaboration across teams and stakeholders

Skills

Required

  • Java 8+
  • Multi-threading
  • Spring Boot
  • Kafka
  • Active MQ
  • RESTful HTTP
  • Oracle/MySQL
  • AWS/Private Cloud
  • Docker/Kubernetes
  • leading teams of technologists
  • hiring, developing, and recognizing talent
  • leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools
  • defining governance/ways of working (human-in-the-loop validation, quality gates)
  • measuring outcomes
  • ensuring secure handling of sensitive inputs/outputs
  • Strong understanding of responsible AI use in engineering workflows
  • data sensitivity considerations
  • resiliency/security implications
  • control expectations
  • coach managers/leads and influence leaders on safe scaling patterns
  • In-depth knowledge of the services industry and their IT systems
  • Practical cloud native experience
  • Experience in Computer Science, Engineering, Mathematics, or a related field and expertise in technology disciplines
  • Formal training or certification on software engineering concepts
  • 5+ years applied experience
  • 2 + years of experience leading technologists

Nice to have

  • Experience working at code level
  • Knowledge of Payments in Banking domain

What the JD emphasized

  • enterprise-authorized AI-assisted engineering
  • enterprise-authorized AI-assisted development
  • responsible AI use