Director of Software Engineering - Java, AWS - Equities or Securities Lending

in Bengaluru India. If you are a software engineering leader ready to take the reins and drive impact, we’ve got an opportunity just for you. As a Director of Software Engineering at JPMorganChase within the Corporate and Investment Banking, you lead a technical area and drive impact within teams, technologies, and projects across departments.

Utilize your in-depth knowledge of software, applications, technical processes, and product management to drive multiple complex projects and initiatives, while serving as a primary decision maker for your teams and be a driver of innovation and solution delivery.

, AI-orchestrated delivery workflows, release readiness controls, automated test modernization, and incident triage acceleration), while establishing guardrails for validation, security, resiliency, traceability, and reuse across teams.

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 and support capacity unlock initiatives at scale. Required

qualifications, capabilities, and skillsFormal training or certification on software engineering concepts and 10+ years of applied experience.

In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertiseExperience developing or leading cross-functional teams of technologists with the help of AIExperience with hiring, developing, and recognizing talentExperience leading a product as engineering leadExperience in JAVA Micro services, Spring boot Practical cloud native experience - Experience in Kubernetes, AWS (EKS, EC2) is mustDeep hands-on experience with Spring framework, Object Oriented methodology of design and development, and Spring Batch frameworkExperience leading adoption of agentic AI-enabled engineering practices (using enterprise-authorized tools within the work environment) across teams, including defining operating expectations (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.

Strong understanding of responsible AI use and control expectations in engineering workflows, including data sensitivity, resiliency/security implications, and governance; ability to influence leaders on safe scaling patterns and reuse. Experience in Equities/ Stock Borrow Loan domain is requiredPreferred

qualifications, capabilities, and skillsExposure to agile methodologies such as CI/CD, Applicant Resiliency, and SecurityHands-on practical experience in system design, application development, testing, and operational stability.