Placer.ai is seeking a Senior AI Platform Engineer to build and operate the internal AI platform that powers the company. This role encompasses designing and shipping AI tooling, agents, connectors, automation, and the infrastructure that lets the entire organization accelerate productivity. You will work with Claude and Databricks as the backbone of the internal AI stack and drive deeper integrations to enable agentic, high-leverage workflows across the business. The position is remote in the United States and reports to the COO, partnering with AI Operations, R&D, Data Science, GTM, and other teams, owning the path from integration requests to production-grade systems. Responsibilities include designing and orchestrating agents that perform tasks end-to-end; building MCP servers for external SaaS integrations and internal tools; implementing secure OAuth and credential management; defining production-ready standards for MCP servers, security, logging, and access controls; triaging connector requests and bugs; developing Cowork plugins and Claude skills; owning the Databricks-based Data Platform, and tracking usage to inform decisions. Required: 8+ years of backend engineering; experience with MCP servers, LLM tool use, or AI agent frameworks; experience in data engineering or analytics tooling; strong knowledge of REST APIs, OAuth 2.0, and Google Cloud auth patterns; experience deploying services to Kubernetes; familiarity with Databricks a plus; ability to operate without a fixed playbook; strong communication; ability to balance priorities across R&D Architecture, AI En

Placer.ai is seeking a Senior AI Platform Engineer to build and operate the internal AI platform that powers the company. This role encompasses designing and shipping AI tooling, agents, connectors, automation, and the infrastructure that lets the entire organization accelerate productivity. You will work with Claude and Databricks as the backbone of the internal AI stack and drive deeper integrations to enable agentic, high-leverage workflows across the business. The position is remote in the United States and reports to the COO, partnering with AI Operations, R&D, Data Science, GTM, and other teams, owning the path from integration requests to production-grade systems. Responsibilities include designing and orchestrating agents that perform tasks end-to-end; building MCP servers for external SaaS integrations and internal tools; implementing secure OAuth and credential management; defining production-ready standards for MCP servers, security, logging, and access controls; triaging connector requests and bugs; developing Cowork plugins and Claude skills; owning the Databricks-based Data Platform, and tracking usage to inform decisions. Required: 8+ years of backend engineering; experience with MCP servers, LLM tool use, or AI agent frameworks; experience in data engineering or analytics tooling; strong knowledge of REST APIs, OAuth 2.0, and Google Cloud auth patterns; experience deploying services to Kubernetes; familiarity with Databricks a plus; ability to operate without a fixed playbook; strong communication; ability to balance priorities across R&D Architecture, AI En