Lead Infrastructure Engineer- ANS Risk Remediation
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 JPMorgan Chase within the Infrastructure Platforms team, you apply deep knowledge of software, applications, and technical processes within the network 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
- Own network risk identification and remediation across firewalls, proxies, routers, switches, load balancers, and related platforms.
- Assist with Audit RFIs, ensuring timely and accurate responses to audit inquiries.
- Drive execution end-to-end—prioritizing work, ensuring timely follow-through, and managing stakeholders—while clearly presenting status, risks, and decisions to senior leadership.
- Lead risk remediation initiatives, pinpointing root causes and executing effective solutions.
- Establish operational excellence: runbooks, standards, diagrams, and repeatable controls that are audit-ready.
- Build and maintain KRIs/KPIs and dashboards for leadership reporting (exposure, SLA adherence, control health).
- Partner across Cyber, Technology, and Operations to reduce operational, cyber, data, and resiliency risk.
- Strong ability to communicate complex risk concepts clearly and effectively to diverse audiences, including senior management and external stakeholders.
- 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.
Required qualifications, capabilities, and skills
Formal training or certification on infrastructure disciplines 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
- Hands-on experience in network infrastructure/network engineering with demonstrated leadership.
- Hands on experience in enterprise level security products like firewalls, proxies, load balancing and core networks.
- Experience in leading change management initiatives, particularly in implementing new risk management frameworks or processes.
- Proven ownership of risk remediation workflows (tickets/findings), including tracking, reporting, and sustainable closure.
- Strong working knowledge of enterprise networking and security controls (firewalls, switching/routing, proxies, load balancing).
- Experience operating in regulated environments with high change discipline (ITSM, CMDB, audit support).
- Ability to produce clear executive-facing reporting (KRIs/KPIs, dashboards) using tools such as Excel/PowerPoint; familiarity with SQL and Tableau/Power BI
- 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.
- Bachelor’s in Computer Engineering/CS (or equivalent experience).
- Risk/controls exposure and tooling familiarity (e.g., Archer or similar GRC platforms).
- Relevant certifications (network/security or risk fundamentals) and continuous learning in risk and resilience.