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Alchemy

Cloud Infrastructure Engineer

San Francisco (Remote)$135k–$240kfulltimemidAdded 1 month ago

About this role

Alchemy seeks an experienced Cloud Infrastructure Engineer to design and operate scalable, multi-region Kubernetes infrastructure supporting their blockchain developer platform. You'll lead reliability initiatives, build AI-powered infrastructure tooling, and mentor the team while ensuring cost efficiency and security across billions of daily requests.

What you'll do

  • Architect and operate scalable Kubernetes infrastructure with Terraform across multi-region cloud deployments
  • Drive AI enablement across engineering tools and workflows using Claude, Cursor, and agentic development practices
  • Build AI-powered automation for infrastructure tasks like K8s upgrades, IaC analysis, and cost optimization
  • Develop observability frameworks using Prometheus and Grafana with SLI/SLO enforcement and incident management
  • Design multi-cloud network architecture including VPC, DNS, cross-cloud connectivity, and service mesh configuration
  • Provide technical leadership and mentorship to elevate team operational capabilities

What they're looking for

  • Kubernetes and container orchestration
  • Terraform and Infrastructure-as-Code
  • Cloud platforms (AWS/GCP)
  • Observability tools (Prometheus, Grafana, OpenTelemetry)
  • Multi-region architecture and networking (VPC, DNS, IPAM)
  • GitOps workflows and automation
  • SRE/reliability practices and SLO frameworks
  • Service mesh technologies (Istio)

Benefits

  • Medical, dental, and vision coverage
  • Home office build-out budget
  • Learning and development stipend
  • Wellness programs including gym reimbursement and mental health support
  • Company-sponsored conferences and events
  • Competitive salary with equity, 401k, and flexible time off
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Alchemy

Alchemy builds a blockchain developer platform that provides infrastructure and services for crypto and wallet applications, handling billions of daily requests. The company is hiring software engineers, infrastructure specialists, data engineers, and customer-facing technical roles to support its platform scaling, customer success, and internal AI and data initiatives.

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Likely interview questions

  • Walk us through a time you designed and operated a multi-region Kubernetes infrastructure at scale. What were the key challenges with failover and consistency?
  • Describe your experience implementing SLO frameworks and error budgets across services. How did you handle trade-offs between reliability and feature velocity?
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