You belong to the top echelon of talent in your field. At one of the worlds most iconic financial institutions, where infrastructure is of paramount importance, you can play a pivotal role.
As an Infrastructure Engineer III at JPMorganChase within the Commercial & Investment Bank Payments Technology team, you utilize strong knowledge of software, applications, and technical processes within the infrastructure engineering discipline. Apply your technical knowledge and problem-solving methodologies across multiple applications of moderate scope.
Job responsibilities
Applies technical knowledge and problem-solving methodologies to projects of moderate scope, with a focus on improving data and systems running at scale, and ensures end to end monitoring of applications
Uses enterprise-authorized AI capabilities within the work environment to accelerate monitoring and capacity analysis and documentation, validating outputs and handling operational data according to sensitivity and security requirements.
Resolves most nuances and determines appropriate escalation path
Executes conventional approaches to build or break down technical problems while considering upstream and downstream data and systems or technical implications
Drives the daily activities supporting the standard capacity process applications and partners with application and infrastructure teams to identify potential capacity risks and govern remediation statuses
Accountable for making significant decisions for a project consisting of multiple technologies and applications
Applies reuse-first, AI-assisted approaches to identify recurring capacity risks and improve remediation workflows, ensuring changes are validated and aligned to resiliency and security expectations.
Required qualifications, capabilities, and skills
Formal training or certification on infrastructure engineering concepts and 3+ years applied experience
Hands-on experience in DevOps, with a strong focus on Jenkins, Kubernetes, and SDLC pipelines.
Proven experience in deployment architecture and cloud best practices.
Working knowledge of Linux systems (preferably RHEL), including strong command-line skills for day-to-day engineering and troubleshooting.
Experience with managing EOL components and driving process improvements.
Proficient in Git branch management and infrastructure security. Knowledge of setting up and managing Kafka and Elasticsearch, including their resiliency.
Experience with Helm for Kubernetes package management.
Experience with monitoring and observability tools like Grafana, Dynatrace, Splunk, DataDog, etc
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.
Preferred qualifications, capabilities, and skills
Experience in financial services or a related industry.
Certifications in cloud platforms (e.g., AWS, Azure, Google Cloud).
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