AWS Cloud Lead Infrastructure Engineer - Technical Solutions Engineering

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 100,000 - 130,000; Full time

Job summary

JPMorgan Chase & Co. seeks a Cloud Engineer to join its Cloud Foundational Platforms team in Jersey City, NJ. You will apply your expertise in infrastructure engineering to deliver excellence in technical solutions and project management while collaborating with various engineering teams.

Ideal candidates will have over 5 years of experience in the field and in-depth knowledge of cloud infrastructure and technologies, particularly AWS. This position may require 24/7 on-call support across multiple time zones.

Qualifications

• 5+ years of applied experience in infrastructure engineering.
• Deep knowledge of hardware, networking terminology, databases, and storage engineering.
• Familiarity with large distributed systems.

Responsibilities

• Apply technical expertise to moderate scope projects.
• Drive infrastructure engineering workstreams and projects.
• Manage stakeholder relationships according to compliance standards.

Skills

Infrastructure engineering concepts

Cloud infrastructure

AWS certifications

Scripting languages (e.g., Python)

Kubernetes

Job description

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.

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