Senior Cloud Infrastructure Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Cloud Infrastructure Engineer based in the United States. The Senior Cloud Infrastructure Engineer will design, build, and operate the cloud infrastructure powering a modern, cloud-native SaaS platform. This hands-on engineering role focuses on Google Cloud Platform (GCP), Google Kubernetes Engine (GKE), Kubernetes cluster operations, Terraform, and cloud networking. You will own critical infrastructure foundations, ensuring security, reliability, scalability, and cost efficiency across production environments. Working closely with Platform Engineering, Site Reliability Engineering (SRE), and Security teams, you will improve infrastructure automation, observability, and operational resilience. The role offers opportunities to solve complex technical challenges, influence architectural decisions, and mentor fellow engineers. This fully remote US opportunity is ideal for an infrastructure specialist who enjoys deep technical ownership and building robust systems at scale. Accountabilities:

Cloud Infrastructure Engineering: Design, build, operate, and maintain production infrastructure on Google Cloud Platform, including GKE, VPC networking, load balancers, Cloud DNS, IAM, and related cloud services.

Kubernetes Cluster Management: Own the architecture and lifecycle of production Kubernetes clusters, including provisioning, upgrades, node pool management, autoscaling, networking, capacity planning, and troubleshooting.

Infrastructure as Code: Develop and maintain reusable Terraform modules, infrastructure-as-code frameworks, and automated provisioning workflows to ensure infrastructure changes are consistent, repeatable, and reliable.

Cloud Networking: Design and manage VPCs, subnetworks, firewall rules, routing, Cloud NAT, load balancing, and connectivity across services and environments.

Technical Troubleshooting: Diagnose and resolve complex infrastructure issues involving Kubernetes, Linux, DNS, networking, cloud services, and distributed systems using systematic debugging and production diagnostics.

Observability and Monitoring: Improve infrastructure visibility through Prometheus, logging platforms, metrics, alerting, and related monitoring tools.

Security and Access Management: Implement and maintain infrastructure security controls, including IAM policies, service accounts, secrets management, least-privilege access, Kubernetes RBAC, and network policies.

Reliability and Optimization: Drive improvements in infrastructure availability, scalability, performance, capacity planning, and cloud cost efficiency.

Infrastructure Upgrades and Migrations: Plan and execute Kubernetes and GCP upgrades, migrations, and architectural improvements while minimizing production risks and service disruption.

Cross-Functional Collaboration: Partner with Platform Engineering, SRE, and Security teams to establish scalable infrastructure standards, improve operational practices, and clarify technical ownership.

Technical Leadership: Contribute to architecture discussions and technical design reviews, mentor other engineers, and promote improvements in reliability, maintainability, and engineering quality.

Requirements:

Professional Experience: At least three years of hands-on production experience designing, provisioning, operating, and troubleshooting cloud infrastructure.

Google Cloud Platform: Strong knowledge of GCP services and networking, including VPCs, subnets, firewall rules, routing, Cloud NAT, Cloud DNS, Cloud Load Balancing, projects, IAM policies, service accounts, and security configurations.

Kubernetes and GKE: At least three years of hands-on experience operating production Kubernetes clusters, preferably GKE. Experience must include cluster provisioning, administration, upgrades, and infrastructure-level troubleshooting; deploying applications into existing clusters alone is not sufficient.

Kubernetes Architecture: Strong understanding of control planes, worker nodes, scheduling, networking, services, ingress, storage, resource management, node pools, autoscaling, resource requests and limits, and cluster capacity.

Infrastructure as Code: At least three years of professional Terraform experience managing production cloud infrastructure, developing reusable modules, handling remote state, and implementing safe change-management processes.

Automation and Version Control: Proficiency in scripting with Python, Go, Bash, or similar languages, along with experience using Git-based infrastructure workflows, code reviews, and automated validation.

Linux and Networking: Strong Linux systems administration and troubleshooting skills, combined with a solid understanding of TCP/IP, DNS, TLS, routing, firewalls, and load balancing.

Diagnostics and Problem-Solving: Ability to investigate complex infrastructure issues using logs, metrics, traces, packet-level analysis, and structured debugging techniques.

Production Engineering: Experience designing secure, resilient, and scalable infrastructure for production workloads.

Advanced Experience Preferred: Eight or more years of professional engineering experience and a background operating GKE clusters in large-scale, multi-cluster, or multi-region environments.

Advanced GCP and Kubernetes Skills Preferred: Experience with GKE networking, Workload Identity, Gateway API, Ingress controllers, cluster autoscaling, multi-project GCP architectures, centralized networking, IAM governance, and infrastructure guardrails.

Monitoring and Security Preferred: Experience operating Prometheus, Grafana, and centralized logging infrastructure, along with implementing Kubernetes RBAC, network policies, workload identity, and secrets management.

Scale and Reliability Preferred: Experience executing major infrastructure migrations with minimal disruption, optimizing cloud costs, modeling capacity, and supporting highly available SaaS platforms or distributed systems at significant production scale.

Technical Leadership Preferred: Demonstrated ability to mentor senior engineers and improve infrastructure architecture, engineering practices, reliability, and maintainability.

Work Authorization: Must be authorized to work for any employer in the United States. Current or future employment visa sponsorship is not available.

Benefits:

Annual Salary: US hiring range of $150,000–$175,000, with placement depending on geographic location, professional experience, education, and skill level.

Comprehensive Healthcare: Medical, dental, and vision coverage.

Retirement Benefits: 401(k) plan.

Wellness: Wellness benefits and additional employee support programs.

Remote Work: Remote opportunity within the United States.

Meaningful Technical Impact: Direct ownership of cloud infrastructure and the opportunity to shape GCP and Kubernetes architecture for a cloud-native SaaS platform.

Collaborative Environment: Work alongside experienced professionals across Infrastructure, Platform Engineering, SRE, and Security.

Professional Growth: Opportunities to tackle challenging engineering problems, influence technical decisions, mentor colleagues, and improve systems as the platform scales.

Inclusive Workplace: Equal opportunity employment with a commitment to a collaborative and inclusive culture.

How Jobgether works: We use an

AI-powered matching process

to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Data Privacy Notice:

By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.