Infrastructure Engineer III

JPMorganChase•Plano, TX

About The Position

As an Infrastructure Engineer III at JPMorganChase within the Corporate Sector – Infrastructure Platforms, you will apply strong knowledge of software, applications, and technical processes across infrastructure engineering projects of moderate scope. The role focuses on improving data and systems operating at scale, ensuring end-to-end application monitoring, and making significant technical decisions across projects involving multiple technologies and applications. You will use enterprise-authorized AI capabilities to support monitoring, capacity analysis, documentation, and operational workflows, validating AI outputs and handling operational data according to security and sensitivity requirements. The role also involves building controlled, monitored agentic automation for workflows such as triage, runbook execution, incident summarization, and change validation. You will champion site reliability practices, use data-driven analysis to improve service levels, and collaborate with technical teams, stakeholders, and customers to define service level indicators, objectives, and error budgets. You will analyze telemetry, design dashboards, diagnose and resolve issues, modernize processes, and partner with application and infrastructure teams to identify and remediate capacity risks while maintaining reliability, performance, and security.

Requirements

Formal training or certification in infrastructure engineering concepts and at least 3 years of applied experience.
Demonstrated experience using enterprise-authorized AI capabilities for infrastructure engineering workflows, with strong validation habits and awareness of data sensitivity.
Ability to review and validate AI-assisted recommendations before implementation, escalate when uncertain, and ensure outcomes meet resiliency, security, and auditability expectations.
Strong knowledge of one or more scripting languages.
Experience with multiple cloud technologies and the ability to operate in and migrate across public and private clouds.
Proficiency in scripting, automation, and infrastructure as code, including technologies such as Python, PowerShell, Ansible, and Terraform.
Fluency in at least one programming language, such as Python, Go, Shell Scripting, or .NET, and hands-on experience applying AI-assisted automation and agentic patterns to engineering or operational workflows.
Hands-on ability to use GitHub Copilot and coding assistants to accelerate skill development and build AI agents or workflows for infrastructure operations tasks such as triage, automation, and runbook execution.
Knowledge of infrastructure engineering areas such as Linux or Windows operating systems, networking terminology and protocols, databases, deployment practices, and automation.
Familiarity with web products such as Apache, Tomcat, IIS, or WebSphere/IHS.
Deep proficiency in reliability, scalability, performance, security, enterprise system architecture, toil reduction, and related best practices, with demonstrated ability to implement them within a platform.
Advanced knowledge and experience in observability, monitoring, alerting, and telemetry collection using tools such as Grafana, Dynatrace, Datadog, Prometheus, CloudWatch, or Splunk.
Experience designing and implementing monitoring dashboards using Splunk or Dynatrace, including effective production support.

Nice To Haves

Experience implementing CI/CD pipelines, conducting code reviews using GitHub, and automating processes with Python and scripting.
Hands-on experience and certifications in AWS, Azure, GCP, or other cloud environments; AWS or Azure exposure with understanding of resiliency, scalability, observability, and monitoring.
Experience using Terraform or other infrastructure-as-code technologies for cloud resource management.
Experience supporting complex, mission-critical applications involving multiple components across different technology generations.
Familiarity with modern front-end technologies and experience designing, developing, and implementing software solutions.
Strong drive to expand infrastructure engineering knowledge across emerging technologies and domains, including self-education and evaluation of new technology.

Responsibilities

Apply technical knowledge and problem-solving methodologies to projects of moderate scope, improving data and systems running at scale and ensuring end-to-end application monitoring.
Use enterprise-authorized AI capabilities to accelerate monitoring, capacity analysis, and documentation, validating outputs and handling operational data according to sensitivity and security requirements.
Make significant technical decisions for projects involving multiple technologies and applications.
Use reuse-first, AI-assisted approaches to identify recurring capacity risks and improve remediation workflows, validating changes against resiliency and security expectations.
Build agentic automation for operational workflows such as triage, runbook execution, incident summarization, and change validation, with appropriate controls and monitoring.
Champion site reliability practices and lead data-driven initiatives to improve reliability, stability, and service levels.
Collaborate with team members, technical experts, stakeholders, and customers to identify service level indicators and establish service level objectives and error budgets.
Diagnose and implement changes to resolve issues, modernize technology processes, and provide end-to-end application monitoring.
Collect and analyze monitoring and telemetry data in test and production environments; design and implement dashboards; and ensure system reliability, performance, and security.
Escalate issues with detailed technical write-ups and partner with application and infrastructure teams to identify and remediate capacity risks.
Understand platform interdependencies and limitations.