Role : Cloud Infrastructure Architect
Location : Hybrid-4 days a week in Redwood City, CA
Full time
We need a senior or staff-level engineer with 4+ years of experience in cloud infrastructure who is equally strong at hands-on coding and systems design. You should be comfortable working in a small, fast-moving team with high ownership and minimal red tape, and have a track record of building and operating scalable, reliable cloud infrastructure. You must have a CS or engineering degree and be proficient in Python — this is a Python-heavy environment.
Role Requirements
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Cloud Infrastructure Engineer needed to join a growing team.
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Must handle both coding and systems design; Python, Terraform, and Kubernetes expertise required.
Candidate Requirements
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4+ years of experience preferred; strong coding skills necessary.
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Must have a computer science or relevant engineering degree.
Team Structure and Reporting
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Reports to VP of Engineering; flat structure beyond that.
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Small engineering team of about 20, offering broad exposure across the stack.
Work experience
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Cloud infrastructure engineering at production scale (not just backend/microservices)
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Designing and operating highly available, scalable infrastructure systems
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Managing Kubernetes-based systems for compute workloads
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Implementing infrastructure-as-code across environments
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Education
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BS in Computer Science, Electrical Engineering, or related engineering field
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Hard skills
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Strong Python coding ability (not just scripting) + Bash or Go
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Strong Kubernetes, Docker, and containerized architecture expertise
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AWS required; multi-cloud a plus (GCP, Azure, OCI, on-prem)
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Infrastructure-as-code (Terraform or Pulumi)
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CI/CD pipelines, monitoring/observability & systems-level debugging
What you'll do:
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Architect and maintain multi-cloud infrastructure (AWS primary, plus GCP, Azure, OCI, on-prem) to support customer deployments across diverse environments
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Define and implement infrastructure-as-code using Terraform or Pulumi, driving best practices across the team
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Design and manage Kubernetes-based systems for model training, inference, and data processing workloads
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Write production-quality Python code daily — this is not a scripting-only role; you'll pass rigorous coding interviews and build real systems
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Optimize CI/CD pipelines and streamline deployment of services across customer environments
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Build monitoring, alerting, and logging systems to ensure high availability and observability
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Collaborate closely with research and engineering teams to provide infrastructure support for training large-scale ML models
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Drive cost-efficiency strategies across compute and storage resources
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Respond to and resolve infrastructure incidents with ownership and urgency
Tech stack
Python, AWS, GCP, Azure, OCI, Kubernetes, Terraform, Pulumi, Docker, Helm, CI/CD, Bash, Go, CloudFormation
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Cloud infrastructure and developer tools startups (fast-moving companies with strong cloud/Kubernetes expertise)
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AI research labs and foundation model companies (teams with large-scale cloud infrastructure for training)
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Cloud-native infrastructure teams at major cloud providers and big tech
