Senior Manager of Software Engineering - ML / Agentic Treasury

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 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