
at J.P. Morgan
Bulge Bracket Investment BanksPosted 5 days ago
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**Sr Manager of Software Engineering - Supply Chain** Steer multiple teams as a Senior Manager, driving software engineering excellence within JPMorgan Chase's Infrastructure Platform Supply Chain. Oversee the lifecycle of software solutions, from design to deployment, ensuring business requirements, compliance, and best practices are met. Key responsibilities include strategy development, team management, risk mitigation, CI/CD pipeline improvement, and partnering with stakeholders. Proven experience in managing software engineering teams, CI/CD, and release management in a corporate or financial services environment is required, along with a strong understanding of software engineering strategy, cloud architecture, and SDLC practices. Lead, mentor, and coach team members, fostering a culture of continuous improvement and collaboration.
- Compensation
- Not specified
- City
- Houston
- Country
- United States
Currency: Not specified
Full Job Description
Location: Houston, TX, United States
Job responsibilities
- Leads, develops, and manages software engineering teams, fostering a culture of inclusion, accountability, technical excellence, continuous improvement, and collaboration
- Establishes and executes engineering strategy, roadmaps, priorities, and delivery plans aligned with business objectives
- Oversees software solution design, development, testing, deployment, and technical troubleshooting across multiple applications and technical domains
- Partners with product and business stakeholders to define priorities, manage scope, resolve dependencies, and ensure predictable delivery
- Oversees release management, deployment coordination, production readiness, change management, and operational stability
- Drives adoption and continuous improvement of CI/CD pipelines, automated testing, infrastructure automation, observability, and secure software delivery practices
- Identifies, assesses, and mitigates technology, delivery, operational, cyber, and regulatory risks
- Ensures the creation and maintenance of architecture, design, risk, control, and delivery artifacts
- Uses data, metrics, and reporting to identify trends, improve engineering performance, and strengthen application and system health
- Leads team adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation to improve delivery speed, quality, and operational outcomes, while setting expectations for human validation, secure handling of inputs/outputs, and consistent use of reusable patterns across teams.
- Formal training or certification on software engineering concepts and 5+ years applied experience. In addition, demonstrated coaching and mentoring experience
- Experience managing, mentoring, and developing software engineering teams in a large corporate or financial services environment
- Demonstrated experience leading software delivery across architecture, application development, testing, deployment, release management, and operational stability
- Strong understanding of software engineering strategy, technical roadmaps, delivery governance, and organizational change
- Experience leading agile teams and managing program increments, delivery dependencies, backlogs, and continuous improvement
- Deep understanding of cloud architecture, virtualization, APIs, data models, event-driven solutions, and modern software frameworks
- Strong knowledge of SDLC practices, CI/CD, DevSecOps, application resiliency, security, and automated testing
- Experience establishing or improving engineering standards, release processes, operational controls, and production readiness practices
- Understanding of technology risk management, governance, regulatory expectations, and control processes
- Experience leading responsible adoption of enterprise-authorized AI-assisted development and delivery tools across engineering teams, including defining ways of working (review/validation expectations), measuring outcomes, and ensuring secure handling of data.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and governance
- Familiarity with modern front-end technologies
- Exposure to cloud technologies and cloud-native architecture
- Experience with enterprise architecture, platform engineering, or large-scale distributed systems
- Experience with release orchestration, DevSecOps tooling, observability, and automated deployment platforms
- Experience managing technology risk, audit activities, controls, or regulatory engagements
- Experience leading engineering organizations through large-scale transformation or modernization initiatives




