Senior Infrastructure Engineer

Description

• Quantum Sky is seeking a Senior Infrastructure Engineer to design, build, and operate the cloud and AI infrastructure behind Project 137, the company's applied-research and IP engine. Reporting to the Director of Infrastructure Engineering, this engineer will own Google Cloud Platform (GCP) and Kubernetes environments that run AI/ML training, inference, and data workloads.

• The role is approximately 85% hands-on engineering and 15% project coordination. The ideal candidate is a senior practitioner with deep GCP expertise, production experience supporting AI workloads, and the organizational discipline to plan and schedule infrastructure work across teams.

• Responsibilities:

Cloud and AI infrastructure

• Design, build, and operate production infrastructure on Google Cloud Platform, including landing zones, VPC networking, Cloud IAM, storage, and organization policy.

• Engineer and scale infrastructure for AI/ML workloads: GPU and TPU capacity, distributed training, model serving and inference, and high-throughput data pipelines.

• Support data-science and research teams on Vertex AI, Kubeflow, and related MLOps tooling, including environment provisioning, model registries, and experiment infrastructure.

• Build and maintain hybrid connectivity between on-premises data-center and cloud environments, including Cloud Interconnect, VPN, DNS, and load balancing.

Kubernetes and platform engineering

• Architect and operate GKE clusters, including GPU node pools, autoscaling, workload identity, networking and ingress, and version upgrades.

• Build reusable platform components and Helm charts that give engineering and research teams self-service access to compute and AI tooling.

• Define and automate infrastructure with Terraform and GitOps practices, using Git as the source of truth for configuration, manifests, and CI/CD pipelines.

Reliability and security

• Implement observability, alerting, and SLOs using Cloud Operations, Prometheus, and Grafana; participate in on-call and lead root-cause analysis on incidents.

• Apply cloud security controls: least-privilege IAM, secrets management, container image scanning, policy-as-code, and software supply-chain protections.

• Plan, build, and test backup and disaster-recovery capabilities for platform and AI workloads.

• Mentor engineers, lead design reviews, and document architecture standards and runbooks.

Project coordination (approx. 15%)

• Plan and schedule infrastructure workstreams, maintaining timelines, milestones, and dependency tracking across engineering, research, and operations teams.

• Organize technical work into clear tasks and priorities, and report progress and blockers to the Director of Infrastructure Engineering.

Qualifications

• Required:

• Education: Bachelor's degree in computer science, engineering, or a related technical field. Equivalent experience considered.

• Experience: 5+ years in infrastructure, platform, cloud, or site reliability engineering, including 2+ years of hands-on production work on Google Cloud Platform.

• Google Cloud: Deep expertise across Compute Engine, GKE, VPC, Cloud IAM, Cloud Storage, Cloud Operations.

• AI infrastructure: Experience supporting AI/ML workloads in production, including GPU or TPU provisioning, training and inference platforms, and MLOps tooling such as Vertex AI or Kubeflow.

• Kubernetes: Production experience operating Kubernetes, including cluster operations, Helm, networking and ingress, RBAC, autoscaling, and upgrades.

• Automation: Strong Terraform and Git-based workflow skills; experience with CI/CD tooling such as Cloud Build, GitHub Actions, GitLab CI, or Argo CD.

• Scripting: Proficiency in Python, Go, or Bash for automation and tooling.

• Networking and systems: Solid understanding of Linux, TCP/IP, DNS, load balancing, and hybrid cloud connectivity.

• Organization: Proven ability to plan, schedule, and track technical work across multiple concurrent workstreams using tools such as Jira or Confluence.

• Communication: Clear written and verbal skills; able to explain technical trade-offs to engineers, researchers, and leadership.

• Desired:

• Google Cloud Professional Cloud Architect, Professional Cloud DevOps Engineer, or Professional Machine Learning Engineer certification.

• Certified Kubernetes Administrator (CKA), Application Developer (CKAD), or Security Specialist (CKS).

• Experience with GPU scheduling and sharing on Kubernetes (NVIDIA GPU Operator, Kueue, or Ray) and large-scale distributed training.

• Familiarity with data-center fundamentals for high-density compute, including power, cooling, and capacity planning.

• Multi-cloud experience with AWS or Azure alongside GCP.

• Location:

• This position is based in [Reston, VA] with a [hybrid / on-site] schedule. Occasional travel of approximately 10-20% to partner sites and data-center locations.

About Quantum Sky

Compensation

• Compensation is unique to each candidate and relative to the skills and experience they bring to the position. The salary range for this position is typically between $175,000-$210,000. This does not guarantee a specific salary as compensation is based upon multiple factors such as education, experience, certifications, and other requirements, and may fall outside of the above-stated range.

Benefits

• Highlights of our benefits include Health/Dental/Vision, 401(k) match, Paid Time Off, STD/LTD/Life Insurance, Referral Bonuses, professional development reimbursement, and parental leave.

• The world the mission operates in is going post-quantum, contested, and machine-speed. Quantum Sky engineers the advantage across cyber, networks, software, and quantum because the mission demands dominance, not parity. We don't follow the map. We draw it.

• At Quantum Sky, we believe that success starts with our people. We foster a collaborative, innovative, and mission-driven environment where every team member plays a critical role in shaping the future of technology. Are you ready to join #TeamQuantumSky?

• Quantum Sky Engineering LLC is an Equal Opportunity Employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, [sexual orientation, gender identity,] national origin, disability, status as a protected veteran, or any characteristic protected by applicable law.