As a Senior Manager of Software Engineering at JPMorgan Chase within the Commercial & Investment Bank - Payments (Data Analytics & Regulatory Compliance) Team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
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
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
-
Hands-on practical experience in system design, application development, testing, and operational stability
- Experience in developing, debugging, and maintaining code in a large corporate environment with Java and Python programming languages and database querying languages (SQL)
- Experience with PostgreSQL
- Experience with AWS
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
- Overall knowledge of the Software Development Life Cycle
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills
- Preferred knowledge with Databricks
- Preferred knowledge with ML Frameworks including Scikit-Learn, PyTorch, Pandas