Overview
As a Director of Software Engineering at JPMorgan Chase within Infrastructure Platforms, you will lead a technical area and drive impact across teams, technologies, and projects. Leveraging your deep expertise in software engineering design, architecture, and technical solutions, you will oversee multiple complex projects and initiatives, serve as the primary decision maker for your teams, and champion innovation and solution delivery. Your leadership will be instrumental in advancing engineering excellence, modernizing enterprise applications, and implementing AI-enabled practices across the organization.
Job responsibilities
- Apply knowledge of tools within the Software Development Life Cycle (SDLC) toolchain, including enterprise-authorized AI-assisted development and automation capabilities.
- Set direction and governance for agentic AI-enabled engineering, driving measurable improvements in speed, quality, and operational outcomes (e.g., AI-orchestrated delivery workflows, release readiness controls, automated test modernization, and incident triage acceleration). Establish guardrails for validation, security, resiliency, traceability, and reuse across teams.
- Lead technology and process implementations to achieve functional technology objectives.
- Make decisions that influence team resources, budgets, tactical operations, and the development of software applications.
- Carry governance accountability for coding decisions, control obligations, and success measures such as cost of ownership, maintainability, and portfolio operations.
- Deliver technical solutions that can be leveraged across multiple businesses and domains.
Influence peer leaders and senior stakeholders across business, product, and technology teams.
- Formal training or certification in software engineering and 10+ years of applied experience, including 5+ years leading technologists to solve complex challenges.
- Deep expertise in designing, developing, and modernizing large-scale enterprise applications with emphasis on scalability, resiliency, security, performance, and maintainability.
- Strong hands-on development experience in Python and other programming languages, with aptitude for quickly adopting new technologies.
- Advanced knowledge of modern software architecture (microservices, distributed systems, API-first, event-driven, cloud-native, domain-driven design, enterprise integration).
- Practical experience with AI-driven engineering, including agentic AI frameworks, GenAI applications, AI-assisted tools, prompt engineering, and MCP-based integrations.
- Demonstrated leadership in adopting agentic AI-enabled engineering practices, setting operating standards, measuring outcomes, and ensuring secure handling of sensitive data.
Proven ability to lead and develop cross-functional teams, including hiring and recognizing talent.
- Experience building full-stack applications using Python, ReactJS, responsive design principles, and reusable component-based architectures.
- Experience with compute platforms such as Kubernetes, containers, and cloud-native engineering practices.
- Experience designing and implementing AI-powered solutions, agent orchestration frameworks, MCP-enabled integrations, RAG architectures, and enterprise-scale automation platforms.
- Passion for continuous learning, technology modernization, mentoring engineers, and driving innovation through AI-enabled engineering practices.