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Senior / Staff Infrastructure Engineer

Apiphany.ai· Engineering
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Hybrid (San Francisco)$160k - $300k + equityfull-timePosted 7mo ago

About the role

Design, build, and operate the infrastructure that powers Apiphany’s intelligence platform, ensuring secure, reliable, and scalable cloud deployments across internal and customer-managed clouds.

Responsibilities

  • Design, build, and operate the cloud infrastructure for the company's intelligence platform.
  • Ensure infrastructure meets latency, availability, and compliance requirements.
  • Guide security posture and implement infrastructure-as-code.
  • Support engineering teams in deploying and maintaining systems.

Qualifications

  • 3-5+ years of experience in cloud infrastructure (GCP preferred; AWS/Azure acceptable).
  • Experience deploying into customer-managed cloud environments and hybrid setups.
  • Strong knowledge of application security (RBAC, ABAC, multi-tenant systems, identity/access frameworks, secrets management).
  • Hands-on experience with Kubernetes, Docker, Helm, and service orchestration.
  • Proficiency with Infrastructure as Code tools like Terraform, Pulumi, or equivalent.
  • Experience designing low-latency, high-throughput systems.
  • Background in monitoring, logging, and observability.
  • Experience building and maintaining CI/CD pipelines for production systems.
  • Skilled in networking (VPCs, peering, firewalls, service meshes).

Skills

Required:Cloud InfrastructureKubernetes, Docker, HelmInfrastructure as Code (Terraform, Pulumi)Application Security (RBAC, ABAC, secrets management)Networking (VPCs, peering, firewalls, service meshes)Monitoring & Observability

Benefits

  • Visa sponsorship.
  • Hybrid work model: 3 days in San Francisco office.
  • 401(k) plan.
  • Medical, Dental, and Vision insurance coverage.
  • Snacks at the office.
  • Paid Time Off (PTO) with flexible vacation policy.
Last updated Apr 23, 2026. Interested? Apply on the company site.

About Apiphany.ai

Billions of engineering & manufacturing data points made actionable

Manufacturing organizations operate on complex and fragmented systems, demanding a blend of technical expertise and strategic planning to ensure products are delivered on time, with high quality, and within budget.

manufacturingengineeringdata analyticsAI
Company profileWebsite

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