Senior Manager of Software Engineering
JPMorgan Chase
- Location
- Hyderabad, Telangana, India
- Work model
- On-Site
- Level
- Senior
- H-1B history
- 1,524 approvals (FY2023)
- Posted
- Aug 28, 2026
Skills
About this role
When you mentor and advise multiple technical teams and move financial technologies forward, it’s a big challenge with big impact. You were made for this. As a Senior Manager of Software Engineering at JPMorganChase within the Consumer and Community Banking, you serve in a leadership role by providing technical coaching and advisory for multiple technical teams, as well as anticipate the needs and potential dependencies of other functions within the firm. As an expert in your field, your insights influence budget and technical considerations to advance operational efficiencies and functionalities.
Job responsibilities
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 Accountable for decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures 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. 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. Ensures successful collaboration across teams and stakeholders. Identifies and mitigates issues to execute a book of work while escalating issues as necessary Provides input to leadership regarding budget, approach, and technical considerations to improve operational efficiencies and functionality for the team Java, Spring, Spring Boot, Micro Services, Web Services SOAP/ReST, SQL, Oracle RDBMS, Design Patterns, Java Messaging, Cloud Foundry, Domain Driven Design, Event Driven Architecture, Docker, Kubernetes, No SQL, Kafka, Cassandra, Test Driven Development Develop and enhance Java-based backend services to support high-volume transaction processing. Build and operate solutions using AWS services (e.g., Aurora Postgres, ECS/Fargate, EC2 as applicable) with a focus on scalability, reliability, and performance. Contribute to solution design by partnering with senior engineers/architects and participating in design reviews to ensure implementations align with technical standards and business needs. Use AI-assisted coding tools (e.g., GitHub Copilot, where approved) to improve development efficiency, testing, and code quality. Follow and promote strong engineering practices (code reviews, CI/CD, testing, observability, documentation) and continuously improve the codebase. Collaborate with product managers and stakeholders to clarify requirements and translate them into technical deliverables. Support security and compliance requirements by applying secure coding practices and adhering to Community Banking standards and applicable regulatory expectations Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 5+ years applied experience . In addition, 2 + years of experience leading technologists to manage and solve complex technical items within your domain of expertise Experience leading teams of technologists. Ability to guide and coach teams on approach to achieve goals aligned against a set of strategic initiatives Experience leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools, including defining governance/ways of working (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs. Strong understanding of responsible AI use in engineering workflows, including data sensitivity