Teams at JPMorganChase

Design and deliver enterprise-grade machine learning systems and AI-powered applications for banking. Build scalable, secure, distributed applications and automated cloud, desktop, and ML pipelines. Apply MLOps practices for versioning, reproducibility, and observability while collaborating with cloud and site reliability engineering teams. Develop reusable libraries and business-critical, data-intensive solutions, aligning machine learning problems with business objectives. The role may include mentoring or people leadership.

Leads the design and operation of highly available, scalable, and observable production infrastructure. Defines SLOs, error budgets, and reliability targets; drives incident response, root-cause analysis, and postmortems; develops automation and deployment tooling; champions monitoring and observability; evaluates platform technologies; and mentors engineers. The role also applies secure AI-assisted engineering practices to improve incident triage, testing, and delivery workflows.

Lead a team of controls professionals to translate AI behavior into actionable controls, prototype scalable AI/automation controls, run red-team exercises, steward AI control standards, and engage senior stakeholders to prioritize and deploy AI-enabled control solutions across Asset & Wealth Management.