Lead Infrastructure Engineer

JPMorgan Chase & Co.; Columbus (OH); On-site; USD 120,000 - 170,000; Full time

Job summary

JPMorganChase is seeking a Lead Infrastructure Engineer to join the Network Services team. You will apply deep knowledge of software, applications, and processes within infrastructure engineering and continuously evolve your technical and cross‑functional expertise beyond your core domain.

The role focuses on delivering infrastructure excellence, driving projects across campus, data center, and WAN, and leveraging AI capabilities to accelerate analysis and documentation while ensuring security

Qualifications

• Senior full‑stack network engineering expertise across campus, data center, and WAN
• Proven ability to lead architecture/design and own outcomes end‑to‑end
• Experience using enterprise‑authorized AI to support infrastructure workflows
• Ability to review and validate AI recommendations for resiliency and security
• Deep knowledge of one infrastructure technology and scripting languages
• Deep knowledge of cloud infrastructure across public and private clouds

Responsibilities

• Applies technical expertise to projects of moderate scope and designs solutions for problems of moderate complexity
• Uses enterprise‑authorized AI to accelerate infrastructure analysis and design documentation
• Drives a workstream or project across multiple infrastructure technologies to implement changes
• Considers data/system implications and advises on mitigations
• Applies reuse-first, AI‑assisted practices to identify recurring issues and ensure traceability and auditability

Skills

Senior network engineer

Cloud infrastructure

AI capabilities

Scripting

Architecture leadership

Job description

Assume a vital position as a key member of a high-performing team that delivers infrastructure and performance excellence. Your role 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 Network Services team, you apply deep knowledge of software, applications, and technical processes within the infrastructure engineering discipline. 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 and executes creative solutions for design, development, and technical troubleshooting for problems of moderate complexity
• 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.
• Drives a workstream or project consisting of one or more infrastructure engineering technologies and works with other platforms to architect and implement changes required to resolve issues and modernize the organization and technology processes
• Strongly considers upstream and downstream data and systems or technical implications and advises on mitigation actions
• 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.

Required qualifications, capabilities, and skills

• Senior full‑stack network engineering expertise with campus, data center, and WAN (routing/switching, segmentation, QoS, DNS/DHCP/IPAM), with proven ability to lead architecture/design, guide implementation, and own outcomes end‑to‑end for major initiatives.
• 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
• 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.
• Deep knowledge of one specific infrastructure technology and scripting languages
• Deep knowledge of cloud infrastructure and multiple cloud technologies with the ability to operate in and migrate across public and private clouds