Note: The job is a remote job and is open to candidates in USA. Placer.ai is hiring a Platform Engineer to own the infrastructure behind its internal AI tools. The role takes AI tools from prototype to production, builds integrations with company systems, and helps scale AI securely and reliably across the business.
Responsibilities
- Own the infrastructure behind Placer’s internal AI tools, from architecture to production
- Take AI tools from prototype to production: secure, reliable, and easy to use
- Build and maintain integrations between AI tools and company systems (e.g., Salesforce, Google Workspace, Slack, data warehouse)
- Run CI/CD, environments, and infrastructure as code for internal AI applications
- Set up access controls, data permissions, and audit logging so teams can move fast safely
- Monitor uptime, adoption, and cost, and use the data to decide what to scale, fix, or retire
- Work directly with teams across the company to turn their needs into working tools
- Evaluate new AI tools and models, and recommend what’s worth adopting
Skills
- 7 + years in production, platform, SRE, or DevOps engineering
- Production experience with Kubernetes and public cloud (GCP or AWS)
- Hands-on with infrastructure as code (Terraform, Pulumi, or similar)
- Strong Python or Go experience
- Hands-on experience integrating LLM APIs or AI services into real workflows
- Solid understanding of identity, access control, and secrets management (SSO/OAuth)
- Comfortable working with non-technical internal customers
- Experience with MCP, agent frameworks, or LLM gateways/observability tools (e.g., LiteLLM, Langfuse, Helicone)
- Integrations with business systems such as Salesforce, Google Workspace, Slack, Gong, or Databricks
- Experience supporting non-engineering internal customers, or in a business-systems / internal-tools team
Benefits
- Work with, and learn from, top-notch talent
- Fully remote
Company Overview
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