Backend Automation Engineer

### Backend / Automation Engineer (AI Systems) **Remote · Contract (Part-Time to Full-Time) · US Eastern Hours Preferred · $8–$12/hr** We build production-grade AI automation systems for property-management companies and SMBs. Not demos. Not slideware. Real systems that run unattended in production. ### Our projects include: * AI-powered email triage * Document and invoice processing * Multi-system data synchronization * Human-in-the-loop review apps * Workflow orchestration and automation * Voice intake systems * Browser automation and scraping where APIs don't exist We move fast, ship end-to-end, and care deeply about reliability. ### Why This Role Exists ### We're growing faster than we can build. We need an engineer who can take a scoped brief, own implementation, and deliver production-ready systems with minimal supervision. You won't be handed isolated tickets or busywork — you'll build systems businesses actually depend on. If you enjoy integrations, debugging ugly APIs, automation reliability, and shipping practical AI systems, this role is for you. ### What You'll Build ### Current flagship engagement: A multi-tenant automation platform for a commercial property-management firm that: * Syncs Rent Manager and Microsoft 365 data into a local datastore * Triages inbound maintenance emails * Determines tenant-vs-landlord responsibility using lease data * Detects utility-cost anomalies * Generates organized audit invoice packages on demand * Routes everything through a human review workflow ### Upcoming systems include: * Twilio + ElevenLabs voice intake * Playwright/Skyvern browser automation * AppFolio and Rent Manager write-backs * AI-assisted operations tooling ### What You'll Own * Build scoped client automation systems end-to-end * Design and harden integration pipelines * Implement retries, idempotency, dead-letter handling, and monitoring * Work with third-party APIs and undocumented edge cases * Build deterministic guardrails around LLM workflows * Write tests and validation fixtures for business logic * Debug real production issues quickly and pragmatically ### Must-Haves * Comfortable shipping with: * Claude SDK * Supabase * Vercel * Git * Strong API integration experience: * OAuth/token auth * Pagination * Webhooks * Rate limits * Retry logic * Reliability mindset: * Idempotency * Failure recovery * Silent-failure detection * Solid data modeling instincts: * Schemas * Upserts * Multi-tenant scoping * Able to work from scoped briefs and deliver independently * Comfortable with AI-assisted development workflows (vibe coding) while still understanding and defending your implementation decisions ### Nice-to-Haves * Microsoft Graph API * Playwright / browser automation * Next.js * PDF/document processing * Multi-tenant SaaS experience * Property-management or fintech domain experience ### How We Work * Async-first, low-meeting environment * Small PRs and clean reviews * AI-assisted engineering is normal * Explicit scope boundaries and ownership * Fast iteration with high accountability We care less about credentials and more about whether you can reliably ship working systems. ### What Success Looks Like in 90 Days * You've shipped at least one production client workflow end-to-end * Your systems run without babysitting * Your PRs are trusted and well-tested * You can take a brief and deliver independently ### Compensation * $8–$12/hour initially * Contract role with path to full-time * Rate increases as responsibility and ownership grow ### How to Apply ### We do not screen on resumes. Instead, complete the short proposal exercise below and submit it. Use any AI tools you want — we care that you understand and can defend your decisions. ### Application Exercise (Required) A US commercial property-management firm uses Rent Manager and Microsoft 365. They want three automations: 1. Triage inbound maintenance emails and determine tenant-vs-landlord responsibility 2. Detect utility-cost anomalies month-over-month 3. Generate organized audit invoice packages on demand ### Your proposal should cover: * Feasibility & technical constraints * Architecture and core design decisions * Data model sketch * How you keep AI outputs trustworthy * Phasing and risk management * Reliability strategy * Estimated effort ranges * Required client access/dependencies ### Optional bonus: A small working spike (e.g. Rent Manager API auth + record pull). Clean and thoughtful beats large and unfinished. Strong submissions may lead directly to a paid trial build. Originally posted on [Himalayas](https://himalayas.app)