Omar Diaz

The Revenue Systems Engineer: Commercial Context, Full Technical Ownership

I am a self-taught Revenue Systems Engineer with a deep background in sales, direct response marketing, and production backend development. Pure developers do not live in conversion rates and spam filters. Pure marketers are trapped with brittle, expensive point-and-click tools that break on rate limits. I live at that rare intersection: I understand what makes a prospect buy, and I write the production Python, SQL, and TypeScript that automates the entire revenue pipeline. I am open to joining a remote team where this is core work.

As a U.S. Marine Corps combat veteran, I operate on fail-closed principles: deterministic software owns state and verification, while AI models operate as bounded specialists. I take full architectural ownership of what ships, how it behaves, and how it performs in production.

Slow reply handling is lost revenue. A buyer says yes at 6:47 AM and sits unseen until afternoon. I build automated triage and dispatch routing so high-intent buyers get answered in 3 minutes while buying intent is peak, with fail-closed checks so bad sends stop instead of going out twice.

What I can own

• Bridge growth strategy and technical execution: translate sales copy, market signals, and customer journeys into automated software systems.
• Connect customer intake, research pipelines, internal job queues, and delivery across external APIs.
• Build Python and Node.js queue workers with atomic leasing, idempotency, retries, and fail-closed review gates.
• Own reply-handling and deliverability copy: intent sorting, campaign segmentation, primary-inbox subject lines, and spam-trigger avoidance at volume (up to 36,000 emails/month).
• Ship Next.js interfaces, test API boundaries, enforce telemetry, and operate autonomous daemons with zero downtime.

Proven systems & case studies

Autonomous Outreach & Inbox Deliverability

Case study: Podcast Campaign & Executive Outreach
Built the reply-handling logic behind cold email programs of up to 36,000 emails a month: sorts every reply by intent, groups prospects into the right campaigns, and routes each conversation to the next step. About 85-90% of routine traffic clears at Tier 1. Fail-closed checks keep double sends out. Rotating domains, SPF/DKIM/DMARC, and primary-inbox placement support the volume. Used to interview 300+ manufacturing CEOs.

Automated Transaction Intelligence

Case study: Funding Shortlist
Architected an automated scraping and enrichment ETL pipeline ingesting daily SEC EDGAR Form D filings, normalizing XBRL data, and generating verified investor dossiers. Replaces expensive legacy database subscriptions with fresh, proprietary deal flow every weekday morning.

Multi-Channel Automated Media Production

Case study: Systems Behind America
Built reusable media pipelines that turn 1 core piece of content into 8 platform-ready packages. Enforces computer-vision QC gates with FFmpeg prior to autonomous distribution, saving 20+ hours of manual editing per week.

Autonomous Federal Procurement Intelligence

Case study: RFQWire
Engineered real-time procurement pipelines tracking daily federal defense, textile, and SAM.gov solicitations for manufacturing clients. Enables businesses to launch and scale authoritative daily industry briefings on complete autopilot.

Catalog Parsing & Content Experimentation

Case study: Cart Confirmed
Engineered automated product catalog ingestion, revision tracking, and platform packaging scripts for high-frequency video generation.

How I write and route for the primary inbox

Cold email fails in two places: the inbox filter, and the reply that never gets a clean next step. I write for both.

On the send: subject lines and body copy aimed at the primary inbox. Plain-text formatting. Personalization that names something real about the company. Words and phrases that trip spam filters get cut. Domains rotate. SPF, DKIM, and DMARC are set correctly. The goal is a conversation, not a blast.

On the reply: every response gets sorted by intent (interested, not now, unsubscribe, bounce, out-of-office, booked, human question). Prospects are grouped into the right campaign cohorts. Each thread routes to a next step: calendar, CRM, hold, or stop. About 85-90% of routine traffic clears at Tier 1 so expensive models only see real humans. Fail-closed checks and idempotency mean a bad or duplicate send does not go out.

I have run this at up to 36,000 emails a month. The number matters less than the routing staying accurate when the volume is high.

Smartlead is preferred. Instantly has been used. Stripe, Cal.com, SEC EDGAR, LLM APIs, GoHighLevel, and Clay plug in the same way: if it has an API, it wires into the fail-closed harness.

chris_queue (judgment queue)

A durable job queue on PostgreSQL and SQLite. Workers claim a job with an atomic lease, renew the lease while work runs, and return expired leases so the same work does not double-run. Exponential backoff and dead-letter handling keep failures visible. Dedupe keys stop the same event from entering twice. 3,800+ background jobs processed.

Fail-closed reply gate (Gates 0-5)

Before a manual or automated reply sends through Smartlead, a multi-stage gate checks real state: unsubscribe and mute, live Cal.com booking, brand-voice rules, 24-hour SHA-256 body idempotency, and visual QC on video attachments when present. Any failed gate aborts. Nothing ships on a guess.

Stripe payments without double provisioning

Checkout sessions and subscription events grant entitlements only after the commercial contract checks out (product, price, currency, live mode, payment state). Idempotency keys and event receipts make sure a paid event never provisions twice.

Tools I wire together

I am platform-agnostic: if the tool has an API, it plugs into the same fail-closed harness of leases, idempotency, and stop-safely gates.

Hiring managers

Download Omar-Diaz-Resume.pdf · Email omar.diaz.jobs@outlook.com · Location: Roosevelt, NY · Remote (U.S.) only · Open to joining a team