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clawdbot-workspace/proposals/2026-02-18-enterprise-ai-voice-api-stealth.md
Jake Shore 9e0397859c Daily backup: 2026-02-18
2026-02-18 23:01:51 -05:00

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Lead Systems Architect: Enterprise AI Voice & API Integration (Stealth Venture)

URL: https://www.upwork.com/jobs/~022023992572648299009 Submitted: 2026-02-18 ~12:43 AM EST Rate: $65/hr ($58.50 after fee) Rate Increase: Never Connects: 20 spent (55 remaining) Score: Hot Lead (80+)

Client

  • Rating: 4.94 (24 reviews)
  • Spent: $31K
  • Location: Stamford, CT, USA
  • Member since: Nov 2014
  • 194 jobs posted, 23% hire rate, 9 active hires
  • Avg hourly rate paid: $23.79/hr (⚠️ low avg but posting goes to $70)
  • Payment verified

Job Details

  • Duration: 3-6 months, 30+ hr/wk
  • Level: Expert
  • Range: $15-$70/hr
  • Contract-to-hire opportunity
  • Skills: Twilio API, API, CRM
  • Competition: 15-20 proposals, 0 interviewing

Cover Letter

SYSTEMS

I build the kind of infrastructure you're describing — voice-to-API pipelines, self-healing workflows, and CRM orchestration engines that handle high-volume transactional data without breaking silently. This isn't a side skill for me; it's what I do full-time.

Most Complex State-Managed Automation: I built an enterprise communication engine that orchestrates real-time voice calls (Twilio/Bland), SMS sequences, and email campaigns triggered by CRM pipeline events. The system manages a finite state machine per contact — tracking call disposition, follow-up cadence, opt-out status, and escalation triggers across channels. Each state transition writes to a centralized log (Supabase) with full audit trail, and the orchestration layer (Make.com + custom webhooks) handles branching logic: if a voice call fails, it falls back to SMS with an LLM-personalized message, then escalates to a human agent if no response within the configured window. The system processes 500+ contacts/day with zero silent failures — every error routes to a dead-letter queue with automatic retry logic and Slack alerting.

API Rate Limit Strategy: For high-volume transactional processing, I implement a three-tier approach:

  1. Token bucket rate limiting at the orchestration layer — requests are queued and released at the API's documented rate ceiling
  2. Exponential backoff with jitter on 429 responses — prevents thundering herd when limits are hit
  3. Circuit breaker pattern — if an API endpoint fails 3x consecutively, the circuit opens and routes to a fallback path (cached data or delayed queue) rather than hammering a degraded service

For this project specifically, I'd implement per-endpoint rate tracking in Supabase with a sliding window counter, so the orchestration layer knows exactly how much headroom remains before hitting limits.

What I bring to this role:

  • Deep Twilio/Bland/Vapi experience for low-latency voice with real-time function calling
  • Production Make.com workflows with proper error routing, not just happy-path automations
  • Advanced prompt engineering for GPT-4o and Claude — I build prompt chains that handle edge cases, not just demos
  • OAuth2 API integration across CRM platforms (HubSpot, ServiceTitan, Salesforce)
  • Self-healing architecture as a default, not an afterthought

I'm US-based (EST), available 30+ hrs/week immediately, and I understand that "hardened infrastructure" means the system works at 3 AM when nobody is watching.

Portfolio: https://portfolio.mcpengage.com