Cloud Engineer (GCP)

Location: On-site in Wilton, Connecticut, United States; a flexible arrangement of up to two remote days per week may be available for eligible roles. The position requires access to controlled technology under United States export regulations, so candidates must be legally authorized to access it before starting.

Company

hirify.global develops and services advanced lithography machines that enable leading chipmakers to produce smaller, more powerful, and energy-efficient microchips.

What you will do

• Architect, deploy, and maintain GCP-based platforms integrating AI/ML services, data pipelines, and automated infrastructure.
• Build and support cloud-native applications, including installation, patching, performance tuning, and systems hardening.
• Implement monitoring, observability, and logging with Splunk and native GCP services.
• Troubleshoot complex distributed systems and provide Tier 1/Tier 2 escalation support for cloud and platform issues.
• Drive CI/CD automation, Git-based workflows, and cloud release management.
• Improve system reliability, performance, cloud cost efficiency, developer experience, and compliance with security and service-level requirements.

Requirements

• Bachelor’s degree in Computer Science, IT, or a related field; a master’s degree is a plus.
• 2–3+ years of experience supporting large-scale software or cloud environments.
• Expertise with GCP services including Compute, IAM, Networking, GCS, Cloud Build, GKE, and AI Platform, plus experience with Azure and hybrid cloud architectures.
• Strong knowledge of Linux, TCP/IP and UDP networking, CI/CD, DevOps tools, Git or SVN, virtualization, storage, VMware, and enterprise hardware.
• Scripting experience with Python, Bash, Perl, and Ruby.
• Willingness and legal authorization to work on-site in Wilton and access controlled United States technology are required. Clean-room work with protective clothing and safety equipment is also required.

Nice to have

• Master’s degree in a related field.
• Experience supporting AI/ML workflows, including model deployment, GPU workloads, or data orchestration.
• Familiarity with Agile/Scrum or SAFe methodologies.

Culture & Benefits

• Collaborative work with engineering and business teams on digital and AI transformation.
• Potential flexible workplace arrangement of up to two remote days per week where role requirements permit.
• Equal opportunity and commitment to an inclusive, diverse workforce.
• Reasonable workplace accommodations are available for applicants and employees with disabilities.