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Job Description:

Google Cloud Infrastructure Support Engineer will be responsible for ensuring the reliability, performance, and security of our Google Cloud Platform (GCP) infrastructure. Work closely with cross-functional teams to troubleshoot issues, optimize infrastructure, and implement best practices for cloud architecture. Experience with Terraform for deploying and managing infrastructure templates. Administer BigQuery environments, including managing datasets, access controls, and optimize query performance. Be familiar with Vertex AI for monitoring and managing machine learning model deployments. Knowledge of GCP’s Kubernetes Engine and its integration with the cloud ecosystem. Understanding of cloud security best practices and experience with implementing security measures. Knowledge of setting up and managing data clean rooms within BigQuery. Understanding of the Analytics Hub platform and how it integrates with data clean rooms to facilitate sensitive data-sharing use cases. Knowledge of DataPlex and how it integrates with other Google Cloud services such as BigQuery, Dataproc Metastore, and Data Catalog.

Key Responsibilities:

• Provide technical support for our Google Cloud Platform infrastructure, including compute, storage, networking, and security services.
• Monitor system performance and proactively identify and resolve issues to ensure maximum uptime and reliability.
• Collaborate with cross-functional teams to design, implement, and optimize cloud infrastructure solutions.
• Automate repetitive tasks and develop scripts to streamline operations and improve efficiency.
• Document infrastructure configurations, processes, and procedures.

Qualifications:

Required:

• Strong understanding of GCP services, including Compute Engine, Kubernetes Engine, Cloud Storage, VPC networking, and IAM.
• Experience with BigQuery and VertexAI
• Proficiency in scripting languages such as Python, Bash, or PowerShell.
• Experience with infrastructure as code tools such as Terraform or Google Deployment Manager.
• Strong communication and collaboration skills.
• Bachelor's Degree in Computer Science or related discipline, or the equivalent in education and work experience

Preferred:

• Google Cloud certification (e.g., Google Cloud Certified - Professional Cloud Architect, Google Cloud Certified - Professional Cloud DevOps Engineer)

Employee Type:
 

UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.

We are looking for 8+years experienced candidates for this role.

Primary Skills:

• Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions.
• Experience in at least 5 projects involving enterprise-level cloud architecture and implementation.
• Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures.
• Hands-on experience in large-scale cloud migration projects.
• Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning.
• Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments.
• Strong experience with VMware technologies such as vSphere, ESXi, and vCenter.
• Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage.
• Experience in responding to RFPs, preparing solution designs, and performing estimations and costing.
• Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads.
• Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation.
• Good understanding of SQL and NoSQL databases.
• Deep expertise in DevOps practices, containerization, and CI/CD pipelines.
• Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus.
• Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA.
• Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS).

Responsibilities include:

• Design, develop, and maintain scalable cloud infrastructure solutions.
• Lead cloud adoption strategies, migration roadmaps, and workload assessments.
• Provide infrastructure expertise to design cloud-native and on-premise solution architectures.
• Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups.
• Ensure infrastructure security, compliance, and adherence to industry best practices.
• Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service.
• Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions.

Certifications:

• AWS/Azure/GCP Architect Certifications
• Kubernetes Certifications (CKA/CKAD)

We are looking for 8+years experienced candidates for this role.

Primary Skills:

• Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions.
• Experience in at least 5 projects involving enterprise-level cloud architecture and implementation.
• Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures.
• Hands-on experience in large-scale cloud migration projects.
• Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning.
• Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments.
• Strong experience with VMware technologies such as vSphere, ESXi, and vCenter.
• Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage.
• Experience in responding to RFPs, preparing solution designs, and performing estimations and costing.
• Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads.
• Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation.
• Good understanding of SQL and NoSQL databases.
• Deep expertise in DevOps practices, containerization, and CI/CD pipelines.
• Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus.
• Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA.
• Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS).

Responsibilities include:

• Design, develop, and maintain scalable cloud infrastructure solutions.
• Lead cloud adoption strategies, migration roadmaps, and workload assessments.
• Provide infrastructure expertise to design cloud-native and on-premise solution architectures.
• Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups.
• Ensure infrastructure security, compliance, and adherence to industry best practices.
• Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service.
• Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions.

Certifications:

• AWS/Azure/GCP Architect Certifications
• Kubernetes Certifications (CKA/CKAD)

We are looking for 8+years experienced candidates for this role. Primary Skills: Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions. Experience in at least 5 projects involving enterprise-level cloud architecture and implementation. Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. Hands-on experience in large-scale cloud migration projects. Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning. Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments. Strong experience with VMware technologies such as v Sphere, ESXi, and v Center. Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage. Experience in responding to RFPs, preparing solution designs, and performing estimations and costing. Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads. Proficient in Infrastructure as Code (Ia C) using tools such as Ansible, Terraform, ARM Templates, and Cloud Formation. Good understanding of SQL and No SQL databases. Deep expertise in Dev Ops practices, containerization, and CI/CD pipelines. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus. Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA. Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS). Responsibilities include: Design, develop, and maintain scalable cloud infrastructure solutions. Lead cloud adoption strategies, migration roadmaps, and workload assessments. Provide infrastructure expertise to design cloud-native and on-premise solution architectures. Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups. Ensure infrastructure security, compliance, and adherence to industry best practices. Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service. Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions. Certifications: AWS/Azure/GCP Architect Certifications Kubernetes Certifications (CKA/CKAD)

We are looking for 8+years experienced candidates for this role.

Primary Skills:

• Minimum 8 years of experience in the design, implementation, and maintenance of infrastructure solutions.
• Experience in at least 5 projects involving enterprise-level cloud architecture and implementation.
• Proven expertise in designing and implementing large-scale microservices architectures, distributed systems, and integration architectures.
• Hands-on experience in large-scale cloud migration projects.
• Experience in setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning.
• Solid experience in data center operations, including the implementation and support of private and hybrid cloud environments.
• Strong experience with VMware technologies such as vSphere, ESXi, and vCenter.
• Hands-on expertise in infrastructure domains including networking, authentication, compute, and storage.
• Experience in responding to RFPs, preparing solution designs, and performing estimations and costing.
• Strong knowledge of Docker and Kubernetes, with hands-on experience deploying ML workloads.
• Proficient in Infrastructure as Code (IaC) using tools such as Ansible, Terraform, ARM Templates, and CloudFormation.
• Good understanding of SQL and NoSQL databases.
• Deep expertise in DevOps practices, containerization, and CI/CD pipelines.
• Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus.
• Experience working on projects with compliance requirements such as GDPR, PCI DSS, and HIPAA.
• Strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS).

Responsibilities include:

• Design, develop, and maintain scalable cloud infrastructure solutions.
• Lead cloud adoption strategies, migration roadmaps, and workload assessments.
• Provide infrastructure expertise to design cloud-native and on-premise solution architectures.
• Architect infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups.
• Ensure infrastructure security, compliance, and adherence to industry best practices.
• Design and implement new capabilities that address gaps and provide an integrated, end-to-end, scalable service.
• Collaborate with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions.

Certifications:

• AWS/Azure/GCP Architect Certifications
• Kubernetes Certifications (CKA/CKAD)