Infrastructure Engineer III

JPMorgan Chase & Co.; New York (NY); On-site; USD 110,000 - 180,000; Full time

Job summary

JPMorganChase is seeking an Infrastructure Engineer III in New York, focused on scalable data and systems, with strong cloud, scripting, and DevOps skills. You will work with AWS/Azure, Python, and modern observability tools to optimize capacity and reliability across multi-technology environments.

The role requires hands-on experience, Agile practices, and collaboration with cross-functional teams to uphold security and resiliency standards.

Qualifications

• Formal training or certification on infrastructure engineering concepts and 3+ years applied experience.
• Strong knowledge of hardware, networking, databases, storage, deployment practices, automation, scaling, and resilience.

Responsibilities

• Applies technical knowledge to projects of moderate scope and ensures end-to-end monitoring of applications.
• Uses AI capabilities to accelerate monitoring and capacity analysis, validating outputs and handling sensitive data.

Skills

Analytical thinking

Communication

Team collaboration

Agile practices

Problem solving

Tools

AWS

Azure

Python

Git

CI/CD

Jira

Tableau

ServiceNow

Splunk

Grafana

Dynatrace

Job description

You belong to the top echelon of talent in your field. At one of the world's 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 Consumer and Community Banking 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 the 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
• Drives the daily activities supporting the standard capacity process applications
• Partners with application and infrastructure teams to identify potential capacity risks and govern remediation statuses
• Considers upstream/downstream data and systems or technical implications
• Be 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
• Strong knowledge of one or more infrastructure disciplines such as hardware, networking terminology, databases, storage engineering, deployment practices, integration, automation, scaling, resilience, and performance assessments
• Hands-on experience with AWS/Azure Cloud platforms and Python or other scripting tools
• Hands-on with Git, CI/CD pipelines, and DevOps deployment practices. Experience with reporting and dashboarding using at least one data visualization platform (e.g., Tableau). Experience with CMDB-type inventory management and reporting tools such as ServiceNow and with any observability platforms such as Splunk, Grafana, Dynatrace.
• Use Agile practices and backlog & prioritization tools such as Jira to plan, build and deliver the work. Turning Manual into automated workflows on a continuous basis
• Knowledge of how infrastructure assets (Cloud, on-prem, private Cloud, SaaS)are registered, stored, and tracked through end-to-end life cycle. Ability to shift from reactive to proactive methodologies to remediate and mitigate security risks. Strong background in Tech Risk & Controls oversight, monitoring, and reporting, with proven ability to execute controls framework activities in partnership with technology and risk stakeholders
• Understanding of ITAM lifecycle governance and how asset inventory and classification impact control effectiveness and findings
• 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.