COMPANY OVERVIEW

We operate one of the most advanced real estate platforms in Canada, with:

• Live MLS data (updated every 15 minutes)
• 145,000+ registered users
• Detailed tables for property views, building views, and user preferences
• Best-in-class map search and advanced filter tools

We’re now taking the next step — building an AI Concierge that talks to users directly on SMS, WhatsApp, and web chat, delivering personalized property alerts, building insights, and market updates in real time.

QUALIFICATIONS

• Required:
• Strong backend development in Python (FastAPI) or Node.js (NestJS/Express)
• Solid MySQL experience with complex queries, joins, and indexing
• Experience integrating with LLM APIs (OpenAI function calling preferred)
• Experience with Twilio (SMS/WhatsApp) or similar messaging APIs
• Understanding of secure API design and parameterized queries
• Nice to have:
• Experience with vector search (OpenSearch, pgvector, Pinecone)
• Knowledge of cron job scheduling and distributed task queues (Celery, Bull, etc.)
• Familiarity with real estate data formats / RETS / MLS feeds
• Basic DevOps (Docker, CI/CD, monitoring)

We’re looking for a Backend Developer with experience in AI integration, MySQL, and messaging APIs to help us launch our next-generation AI-powered real estate assistant. This assistant will:

• Understand user preferences (from search history, property views, building views)
• Automatically send personalized property alerts when MLS changes occur (new listings, price drops, open houses)
• React to market events (rate changes, tax incentives, local developments) with tailored outreach
• Allow users to book showings, compare buildings, and get market insights directly in cha

ROLE SUMMARY

We’re looking for a Backend Developer with experience in AI integration, MySQL, and messaging APIs to help us launch our next-generation AI-powered real estate assistant. This assistant will:

• Understand user preferences (from search history, property views, building views)
• Automatically send personalized property alerts when MLS changes occur (new listings, price drops, open houses)
• React to market events (rate changes, tax incentives, local developments) with tailored outreach
• Allow users to book showings, compare buildings, and get market insights directly in chat

KEY RESPONSIBILITIES

• Database integration: Connect our AI orchestration layer to our existing MLS + user activity database (read-only), using secure, whitelisted SQL queries.
• AI tool building: Expose named query functions (e.g., searchlistings, morelikethis, buildingfacts) for AI to use via function calling.
• Messaging integration: Build Twilio (SMS & WhatsApp) webhook endpoints and routing for inbound/outbound AI conversations.
• Event triggers:
• MLS changes (new listing, price drop, open house) → personalized alerts
• Market events (rate changes, tax incentives, local news) → relevant user outreach
• Personalization logic: Merge explicit user preferences with behavioral data (userlistingviews, userbuildingviews) for ranking.
• Microservices:
• Mortgage impact calculation (payment delta, buying power change)
• Alert dispatcher with throttling, opt-out handling, and channel preferences
• Security & compliance: Implement rate limits, opt-out handling, and logging for all AI/database interactions.
• Testing & monitoring: Write unit/integration tests for all query functions and jobs; set up monitoring for cron jobs.