Production-Ready Gmail to Jobber Request Automation (AI & GraphQL)
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About this role
PHP, Java, Python, Software Architecture, Node.js, JSON, GraphQL, Automation, Database Management, API Integration · Overview: We require a production-grade automation service that monitors an incoming Gmail inbox, reliably extracts structured work-order data using an LLM, and creates fully populated Jobber Requests via Jobber's GraphQL API.
Key Functional Requirements: 1. Ingestion: - Real-time email capture using Gmail API via Google Cloud Pub/Sub webhooks (no inefficient polling). - Robust handling of forwarded/nested email threads to extract the original requester's details, not the forwarder.
2. AI Extraction & Validation: - LLM pipeline (OpenAI/Anthropic) using strict JSON schemas (Structured Outputs / Tool Calling). - Extracted fields: Client Name, Phone, Email, Property Address, Job Title, Work Overview, and Job Notes.
3. Media & Snapshot Engine: - Generate a clean PDF snapshot of the original raw email (HTML-to-PDF via Puppeteer or Playwright). - Extract and forward incoming media/documents (JPEGs, PNGs, PDFs).
4. Jobber Sync: - Query existing clients via GraphQL (`clients` query); match by email or phone. - If not found, execute `clientCreate` mutation. - Create a Jobber Request (`requestCreate` mutation) with all extracted fields, attaching the raw email