Principal AI Platform Engineer — MCP & Connectors

DroneDeploy, Inc.; Austin (TX); Hybrid; USD 198,000 - 273,000; Full time

Benefits offered by this job

Equity compensation

Bonus potential

Hybrid work schedule

Job summary

Procore Technologies is seeking a Principal AI Platform Engineer, MCP & Connectors, to design, build, and operate MCP connectors linking Claude to Procore’s enterprise systems. You will own production MCP servers, ensure secure integrations, and collaborate with Platform & AI teams on scalable architectures.

Based in our Austin, TX office with a hybrid schedule, you’ll implement robust authentication, define interfaces, and drive observability across APIs and data pipelines.

Qualifications

• Strong backend development experience and ownership of production services.
• Experience designing and deploying MCP servers or significant MCP integrations.
• Proficiency in Python or TypeScript/Node.js and REST APIs.

Responsibilities

• Design, build, deploy and maintain MCP servers and connectors linking Claude to enterprise platforms.
• Own production MCP servers, manage versioning, docs, and handoffs.
• Evaluate connectors against architecture requirements and make recommendations.
• Implement OAuth, scopes, token validation, secret storage with strict permissions.
• Define interfaces and input schemas, enforce read/write separation and approvals.
• Build tests and observability for APIs, latency, and dependencies.
• Maintain repos, hosting infra, secrets management, and SSO for AI builder program.
• Manage releases, rollbacks, incidents, and on-call duties.

Job description

Procore Technologies is seeking a Principal AI Platform Engineer, MCP & Connectors, to design, build, and operate MCP connectors linking Claude to Procore’s enterprise systems. You will own production MCP servers, ensure secure integrations, and collaborate with Platform & AI teams on scalable architectures.

Based in our Austin, TX office with a hybrid schedule, you’ll implement robust authentication, define interfaces, and drive observability across APIs and data pipelines.