Platform Engineer - AI Tools

Responsibilities

• Own the infrastructure and architecture behind internal AI tools from prototype through production.
• Build and maintain integrations between AI tools and Salesforce, Google Workspace, Slack, data warehouses, and other company systems.
• Manage CI/CD, environments, and infrastructure as code for internal AI applications.
• Implement access controls, data permissions, secrets management, and audit logging.
• Monitor uptime, adoption, and cost to determine what to scale, fix, or retire.
• Work with teams across the company to turn internal needs into working tools.
• Evaluate AI tools and models and recommend adoption decisions.

Requirements

• Require 7+ years of experience in production, platform, SRE, or DevOps engineering.
• Require production experience with Kubernetes and a public cloud such as GCP or AWS.
• Require hands-on infrastructure-as-code experience with Terraform, Pulumi, or similar tools.
• Require strong Python or Go experience.
• Require hands-on experience integrating LLM APIs or AI services into real workflows.
• Require understanding of identity, access control, secrets management, SSO, and OAuth.
• Require comfort working with non-technical internal customers.
• Preferred experience includes MCP, agent frameworks, LLM gateways, and observability tools such as LiteLLM, Langfuse, or Helicone.
• Preferred experience includes integrations with Salesforce, Google Workspace, Slack, Gong, or Databricks, and work supporting non-engineering internal customers or business-systems/internal-tools teams.

Benefits

• Fully remote work arrangement.
• Competitive salary and excellent benefits.
• Opportunity to take a central role on the COO’s team and work with experienced talent.