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Salary
≈ $155k – $282k per year (Estimated)
Location
In office (Jersey City)
Seniority
Senior · 5+ years exp

Confirmed on the employer's own hiring board on Sep 24, 2026. First seen by Alion on Sep 23, 2026. JPMorganChase scores A on the Alion truth index.

Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

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 Engineeringat 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
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