Senior Cloud Engineer

PragmatikeCambridge, MA
1d

About The Position

Pragmatike is hiring on behalf of a fast-growing AI startup recognized as a Top 10 GenAI company by GTM Capital , founded by MIT CSAIL researchers . We are searching for a Senior Cloud Engineer (Multicloud) with deep, hands-on experience building, operating, and scaling production infrastructure across AWS, GCP, and Azure . You will work directly on the cloud and platform layer supporting large-scale, distributed AI systems used by Fortune 500 customers . This role is ideal for an engineer who has operated real multicloud environments in production—not someone limited to a single provider. You will be responsible for building reliable, scalable systems while navigating the complexity of differing cloud primitives, networking models, and operational trade-offs.

Requirements

  • 5+ years of experience as a Cloud / Platform / Infrastructure Engineer .
  • Hands-on production experience with AWS, GCP, and Azure (deep expertise in at least one).
  • Strong experience running Kubernetes in production across multiple clouds.
  • Strong Terraform experience managing 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.

Nice To Haves

  • Experience supporting AI/ML or data-intensive workloads in production.
  • Exposure to GPU-enabled cloud infrastructure or high-performance compute.
  • Experience with CI/CD automation and release pipelines.
  • Familiarity with compliance requirements (SOC 2, ISO 27001).
  • Startup experience or comfort in fast-moving, ambiguous environments.

Responsibilities

  • Build, deploy, and operate production infrastructure across AWS, GCP, and Azure .
  • Maintain consistent environments using Infrastructure as Code (Terraform preferred).
  • Deploy and operate Kubernetes clusters and containerized workloads across multiple cloud providers.
  • Design and manage cloud networking (VPC/VNet design, peering, load balancing, 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 AI training and inference workloads in multicloud environments.
  • Troubleshoot complex production issues spanning compute, networking, storage, and Kubernetes layers.
  • Collaborate closely with AI, backend, and platform teams to support production systems.

Benefits

  • Competitive salary & equity options
  • Sign-on bonus
  • Health, Dental, and Vision
  • 401(k)
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