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Salary
$137k – $278k per year (Estimated)
Location
In office (Jersey City)
Seniority
Staff
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.

Join JPMorgan Chase's Cloud Foundational Platforms team and assume a vital position as a key member of a high-performing team that delivers infrastructure and performance excellence. In this role you will be instrumental in shaping the future at one of the world's largest and most influential companies.

As a Lead Infrastructure Engineer at JPMorganChase within Corporate-Cloud Foundational Platforms team, you will apply your deep knowledge of software, applications, and technical processes within the infrastructure engineering discipline. In this role you will continue to evolve your technical and cross-functional knowledge outside of your aligned domain of expertise.

Job responsibilities

  • Applies technical expertise and problem-solving methodologies to projects of moderate scope
  • Drives a workstream or project consisting of one or more infrastructure engineering technologies
  • Works with other platforms to architect and implement changes required to resolve issues and modernize the organization and its technology processes
  • Executes creative solutions for the design, development, and technical troubleshooting for problems of moderate complexity
  • Strongly considers upstream/downstream data and systems or technical implications and advises on mitigation actions
  • Uses enterprise-authorized AI capabilities within the work environment to accelerate infrastructure analysis and design documentation, validating outputs and handling operational data according to sensitivity and security requirements.
  • Applies reuse-first, AI-assisted practices within delivery and automation routines to identify recurring issues and validate remediation options, ensuring changes are traceable/auditable and aligned to resiliency and security expectations.
  • Manages stakeholder relationships and the team’s work in accordance with compliance standards, service level agreements, and product supportability requirements
  • Partners with engineering and product teams to ensure remediation/permanent closure of issues and to identify trending issues to drive product improvement
  • Demonstrates a high aptitude for both learning and teaching as product teams are continually releasing new features and products
  • Provides (follow the sun) 24/7 on call support through a distributed team spanning multiple time zones.

Required qualifications, capabilities, and skills

  • Formal training or certification on Infrastructure engineering concepts and 5+ years applied experience
  • Deep knowledge of one or more areas of infrastructure engineering such as hardware, networking terminology, databases, storage engineering, deployment practices, integration, automation, scaling, resilience, or performance assessments
  • Deep knowledge of one specific infrastructure technology and scripting languages (e.g., Scripting, Python, etc.) and AWS certification(s)
  • Drives to continue to develop technical and cross-functional knowledge outside of the product
  • Deep knowledge of cloud infrastructure and multiple cloud technologies with the ability to operate in and migrate across public and private clouds
  • Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity.
  • Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations.
  • A drive to continue to develop technical and cross-functional knowledge
  • Familiarity with working in a large distributed system across a range of technologies including compute, databases, messaging, observability, and telemetry
  • Knowledge of incident, change, and problem management processes and the controls that govern them
  • Understanding of data-driven decision making

Preferred qualifications, capabilities, and skills

  • Kubernetes, Azure, GCP, or Terraform certifications
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