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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Infrastructure Engineer III : NeoVest - **Company:** JPMorgan Chase & Co. - **Location:** Pleasant Grove, UT, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Microsoft Windows, Artificial Intelligence, Amazon Web Services, Confluence, JIRA, Microsoft Azure, Cloud Computing, HP Systems Insight Manager, Linux Servers, Virtual Desktops, Operational Data Store, Release Management, Ansible, Google Cloud, Enterprise Software Applications, Microsoft InTune, Information Technology, Teamcity, Virtual Private Clouds, Jenkins - **Published:** September 19, 2026 - **Apply:** https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/requisitions/preview/210787905 ## About the Role * Formal training or certification on infrastructure engineering concepts and 3+ years applied experience (NAMR/APAC - India/LATAM/Hong Kong) * Supported enterprise application platforms across production and non-production environments, ensuring stability, availability, and consistent operational standards. * Executed controlled deployments, service restarts, version upgrades, and rollback-aware changes with strong attention to detail across multiple environments. * Operated and troubleshot application-hosting infrastructure on Windows and/or Linux servers, applying best practices for reliability, security, and performance. * Followed, maintained, and improved runbooks, release steps, and operational procedures to increase repeatability, reduce risk, and shorten recovery times. * Diagnosed and resolved platform/service incidents under time pressure, prioritizing clear communication, rapid triage, and safe remediation/escalation when needed. * Coordinated effectively with engineering, SRE, infrastructure, networking, release management, and support teams, working within change management and release governance practices. * Used Jira, Confluence, and operational tooling to document and track work, and leveraged enterprise-authorized AI capabilities with strong validation habits and data-sensitivity awareness before implementation. * 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 with multiple cloud technologies (ability to operate in and migrate across public and private clouds - AWS, GCP, Azure) * Experience with CI/CD pipelines and tools e.g. Ansible, Jenkins, TeamCity, Harness.io, Azure DevOps ## Description * Execute configuration, operational changes, and application/platform releases (upgrades, cutovers/rollbacks, packaging/promotion, regional rollouts) across production and lower environments, including post-deployment validation. * Operate and support production reliability through day-to-day support, incident troubleshooting, controlled restarts, environment readiness for maintenance/transitions, and maintaining runbooks/knowledge transfer to reduce key-person dependency. * Manage and support user endpoint devices and applications, including provisioning, standardizing, and supporting VDI/virtual desktops (preferred: M365/Intune/Company Portal and AWS Workspaces). * Apply technical problem-solving to moderate-scope initiatives focused on improving data and systems at scale, ensuring end-to-end application monitoring, and resolving nuances with appropriate escalation when needed. * Drive the standard capacity process by partnering with application and infrastructure teams to identify recurring capacity risks, govern remediation status, and use enterprise-authorized AI to accelerate monitoring/capacity analysis and documentation while validating outputs and handling operational data per security/sensitivity requirements. * 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. * 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. ## Related Videos - [Enterprise-Cloud-Native - Fast-Paced Development & Deployment in a Highly Secure Banking Environment](https://www.wearedevelopers.com/videos/671-enterprise-cloud-native-fast-paced-development-deployment-in-a-highly-secure-banking-environment) - [Dev & Test in the Cloud? 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