Full-Time

Senior Cloud Engineer

Updated on 8/1/2026

Pragmatike

Pragmatike

No salary listed

Cambridge, MA, USA + 5 more

More locations: Boston, MA, USA | California, USA | San Francisco, CA, USA | New York, NY, USA | New Jersey, USA

Hybrid

Remote option is available for out-of-state applicants. Cambridge work follows Eastern Time (UTC−4).

Category
DevOps & Infrastructure (1)
Required Skills
Graphics Processing Unit (GPU)
Kubernetes
Microsoft Azure
Incident Response
Distributed Systems
High Performance Computing (HPC)
Machine Learning
Computer Networking
Infrastructure as Code (IaC)
Docker
SOC 2
AWS
Terraform
DevOps
Google Cloud Platform
Requirements
  • At least 5 years of experience as a Cloud, Platform, or Infrastructure Engineer.
  • Hands-on production experience with AWS, Google Cloud Platform, and Microsoft Azure, with deep expertise in at least one provider.
  • Strong experience running Kubernetes in production across multiple clouds.
  • Strong experience using Terraform to manage multicloud infrastructure.
  • Solid understanding of cloud networking differences and security models across providers.
  • Experience operating distributed systems with on-call ownership.
  • Ability to work across provider-specific services while maintaining consistent abstractions.
  • English proficiency is required.
Responsibilities
  • Build, deploy, and operate production infrastructure across AWS, Google Cloud Platform, and Microsoft Azure.
  • Maintain consistent environments using Infrastructure as Code, preferably Terraform.
  • Deploy and operate Kubernetes clusters and containerized workloads across multiple cloud providers.
  • Design and manage cloud networking, including VPC and VNet design, peering, load balancing, and private connectivity.
  • Implement monitoring, logging, alerting, and incident response for multicloud systems.
  • Optimize performance, reliability, and cost across providers through autoscaling and capacity planning.
  • Support artificial intelligence training and inference workloads in multicloud environments.
  • Troubleshoot complex production issues spanning compute, networking, storage, and Kubernetes layers.
  • Collaborate closely with artificial intelligence, backend, and platform teams to support production systems.
Desired Qualifications
  • Experience supporting artificial intelligence, machine learning, or data-intensive workloads in production.
  • Exposure to GPU-enabled cloud infrastructure or high-performance computing.
  • Experience with continuous integration and continuous delivery automation and release pipelines.
  • Familiarity with compliance requirements such as SOC 2 and ISO 27001.
  • Startup experience or comfort working in fast-moving, ambiguous environments.

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