Lead Infrastructure Engineer

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 the Corporate Sector - Infrastructure Platforms, 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

• Lead architecture and engineering for scalable backup, recovery, immutable-data protection, and recovery-assurance services.

• Drive automation-first, API-led, and self-service capabilities that reduce operational toil and improve customer outcomes.

• 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.

• Build cloud-native solutions using AWS services, infrastructure as code, CI/CD, and modern software-engineering practices.
• Embed SRE principles through reliability metrics, observability, incident learning, operational readiness, and continuous improvement.
• Design preventive and detective security controls, policy guardrails, automated validation, and evidence for regulatory and audit needs.
• Establish standards for enterprise-authorized AI-assisted workflows, including human validation, traceability, resiliency, and secure handling of sensitive data.
• Deliver telemetry, reporting, and operational intelligence for backup health, compliance, and recovery readiness.
• Mentor engineers, influence senior stakeholders, and coordinate cross-team delivery with clear ownership and explicit dependencies.

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

• 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.

• Demonstrated experience building distributed systems, platform services, APIs, automation frameworks, and cloud-native applications.
• Strong knowledge of enterprise data protection, backup and recovery, cyber resilience, immutable storage, retention, and recovery testing.
• Advanced AWS experience spanning backup, IAM, security, observability, and infrastructure automation.
• Proficiency in Python and at least one additional language such as Java, Go, or C#.
• Experience with Terraform or CloudFormation and CI/CD platforms such as Jenkins, GitLab, or GitHub Actions.
• Expertise in SRE practices, monitoring, telemetry, incident management, and production operational readiness; Hands-on experience with observability/monitoring platforms such as Dynatrace and Grafana.
• Ability to lead complex, cross-organizational initiatives and translate security, control, and regulatory requirements into engineered solutions.

Preferred qualifications, capabilities, and skills

• Experience with Cohesity, Commvault, AWS Backup, Kubernetes/OpenShift, database platforms, cyber-recovery solutions, operational analytics, and regulated financial-services environment