Infrastructure Engineer III

Role Overview

As an Infrastructure Engineer III at JPMorganChase within the Commercial & Investment Bank Payments Technology team, you will utilize strong knowledge of software, applications, and technical processes within the infrastructure engineering discipline. You will apply technical knowledge and problem-solving methodologies across multiple applications of moderate scope to improve data and systems running at scale.

Responsibilities

• Applies technical knowledge and problem-solving methodologies to projects of moderate scope, focusing on improving data and systems running at scale and ensuring end-to-end monitoring.
• Uses enterprise-authorized AI capabilities to accelerate monitoring, capacity analysis, and documentation.
• Resolves nuances and determines appropriate escalation paths.
• Executes conventional approaches to build or break down technical problems while considering upstream and downstream implications.
• Drives daily activities supporting standard capacity process applications and partners with teams to identify and govern remediation of capacity risks.
• Accountable for making significant decisions for projects consisting of multiple technologies and applications.
• Applies reuse-first, AI-assisted approaches to identify recurring capacity risks and improve remediation workflows.

Requirements

• Formal training or certification on infrastructure engineering concepts and 3+ years of 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.
• 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, or DataDog.
• Demonstrated experience using AI capabilities within engineering workflows with strong validation habits.

Preferred Qualifications

• Experience in financial services or a related industry.
• Certifications in cloud platforms (e.g., AWS, Azure, Google Cloud).
• Strong communication and collaboration skills.

Skills

• Kubernetes
• Jenkins
• Linux
• DevOps
• Kafka