Sr Manager of Software Engineering - Analytics & Reporting Lead

JPMorgan Chase & Co.; Columbus (OH); On-site; USD 180,000 - 220,000; Full time

Job summary

JP Morgan Chase is seeking a Senior Manager of Software Engineering within Corporate Technology. You will mentor multiple technical teams and provide technical coaching while shaping budget and architectural decisions.

As a senior leader, you will drive enterprise-wide AI-assisted engineering initiatives, establish governance and quality gates, and ensure security, resiliency and reliable delivery across programs.

Qualifications

• Formal training or certification on software engineering concepts with 5+ years applied experience; in addition, 2+ years of experience leading technologists to manage and solve complex technical items.
• 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 considerations, resiliency/security implications, and control expectations; ability to coach managers/leads and influence leaders on safe scaling patterns.
• Experience with hiring, developing, and recognizing talent.
• In-depth knowledge of the services industry and their IT systems.
• Practical cloud native experience.
• Experience working at code level.

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.

Skills

Technical leadership

Software architecture

AI-assisted development

Cloud native

Budget planning

Mentoring teams

Stakeholder collaboration

SDLC governance

Tools

AWS

Terraform

Databricks governance

Job description

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 Corporate Technology, 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. 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. patterns.
• 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.
• 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. patterns.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and control expectations; ability to coach managers/leads and influence leaders on safe scaling patterns.
• Experience with hiring, developing, and recognizing talent.
• In-depth knowledge of the services industry and their IT systems.
• Practical cloud native experience.
• Experience working at code level.

Preferred Qualifications, Capabilities, and Skills

• Experience building data-driven products (analytics, insights platforms, dashboards, experimentation).
• Experience with machine learning frameworks/APIs and designing/implementing RAG pipelines or agentic AI workflows.
• Familiarity with AWS networking (VPC, subnets, routing, security groups), Terraform-based infrastructure deployments, and cost optimization strategies (autoscaling, spot vs. on-demand, auto-termination).
• Experience with RDBMS, NoSQL and Vector Databases and modernizing legacy systems while managing tech debt effectively.
• Background partnering closely with Product/Design, with demonstrated ability to establish UX standards and champion customer-centric, accessible design practices across engineering teams.
• Observability experience for data systems (freshness/completeness metrics, lineage, SLAs, alerting) and Databricks governance (Unity Catalog, catalogs/grants, auditing).
• Familiarity with the financial services industry.