Magna Collective
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CRUZ FLORES IV · PHOENIX, ARIZONA · AVAILABLE FOR ENGAGEMENTS

WHITEBOARD
TO REVENUE

I design and build the data and AI systems companies run on — ETL pipelines, warehouses, and the agent and reporting layers above them. Principal engineer on every engagement, from architecture through production.

Client workWhat I do
Directcruz@magnacollective.xyz
Phone(480) 930-0515
Start an engagement24H RESPONSE
SENT DIRECTLY TO CRUZ · NO MAILING LIST
Portfolio companies
240+
Reporting on pipelines I built
Source systems
5+
Unified per client deployment
Solidity contracts
18
Zero high-severity at audit
Production surfaces
3
iOS · Android · Web
(01)What I doFOUR ENGAGEMENT TYPES

One engineer across the whole stack. Nothing is lost in a hand-off.

01

Fractional CTO

Founders without a technical counterpart · Teams whose roadmap has stalled

I own the architecture, the sequencing, and the trade-offs — then build the system myself. You get an engineer accountable for both the decision and the implementation, not a strategy document.

System architecture
Build vs. buy
Technical hiring
Code review
Roadmap ownership
02

Data Engineering

Data spread across systems nobody can query · Reporting that takes a week

ETL pipelines, data warehouses, and the analytics layer above them. I consolidate CRM, billing, and product systems into one queryable model, then build the reporting your operators use without asking engineering first.

ETL pipelines
Data warehousing
Source-system connectors
Unified data models
Analytics + dashboards
03

AI & Agent Systems

LLM projects that never leave the demo

Agent infrastructure, retrieval, and LLM analytics taken to production with evaluations, cost controls, and human approval gates — including on-device inference where the data cannot leave the hardware.

Agent infrastructure
RAG + retrieval
Evaluation harnesses
Cost + token controls
On-device inference
04

Product Engineering

Software that has to ship to real users on real platforms

Native Swift and Kotlin for mobile, Next.js on Postgres for everything server-side. Offline-first architecture, multi-tenant backends with genuine isolation, and delivery through the App Store and Play.

Swift · SwiftUI
Kotlin
Next.js · TypeScript
Multi-tenant backends
App Store + Play
(02)Client workSELECTED ENGAGEMENTS

Two engagements in full. The brief, the build, and what came of it.

Phoenix Strategy Group

AI & Data Systems Engineer
Aug 2025 — Present
The brief

Phoenix Strategy Group runs full-stack finance and revenue operations for founder-led companies — fractional CFO, M&A, and investment banking across a book of 240+ portfolio companies. Client financial and revenue data sat in disconnected systems, so every reporting question became a manual export.

What I built
  • Built the firm's data engineering practice from nothing — ETL pipelines, data warehouses, and the analytics and dashboard layer that now appears in their service catalog.
  • Wrote the source-system connectors — HubSpot, Salesforce, Square, Zoom, and custom REST and webhook integrations — consolidating fragmented client systems into a single queryable revenue model.
  • Delivered a multi-tenant backend rewrite for a health-tech client platform, including tenant isolation and access control.
  • Productized the AI work into a sellable line: voice and CRM automation, white-labeled sales intelligence, and autonomous lead-generation agents.
Outcome
  • Data engineering is now a standing service line at the firm — pipelines, warehousing, analytics, and dashboards.
  • Led the firm's first open-source release.
  • Moved a fractional CFO practice into shipping AI products.
  • Negotiated the AI practice's commercial terms with the managing partner: monthly retainer plus 60% of net revenue.
240+
Portfolio companies
5+
Source systems unified
1st
Open-source release
60%
Net revenue share
ETLData warehousingAnalyticsMulti-tenantAgents

Growth Capital

Head of AI & Data Systems
Apr 2026 — Aug 2026
The brief

Growth Capital needed an internal dashboard and the data layer beneath it, with executives waiting days on numbers that had to be assembled by hand. The work began as a defined flex engagement with a single deliverable.

What I built
  • Designed and built the data layer and internal dashboard as sole engineer, working directly with executive stakeholders rather than through an analyst layer.
  • Modeled the underlying data so operators could answer their own questions instead of routing every request back through engineering.
  • Set the firm's AI strategy and then implemented it — the same person on the whiteboard and in the repository.
Outcome
  • Expanded from the initial flex engagement into Head of AI & Data Systems.
  • Converted the work into a recurring engineering and SaaS retainer.
1
Flex scope to retainer
4mo
To expanded mandate
0
Layers to the executive
Data layerDashboardsAI strategyExecutive stakeholders
(03)Track recordCURRENT & RECENT
Aug 2026 — Present
RevCentric.ai
Head of AI & Data Systems

Own the AI and data architecture for the revenue intelligence platform, from source-system ingestion through the agent and reporting layer. Building the unified data model that consolidates CRM, billing, and product data into one queryable revenue layer for operators and finance teams.

2025 — Present
Magna Collective
Founder

Agent architecture, automation, and custom LLM systems for clients in Phoenix, San Francisco, and New York. Principal engineer on every engagement.

Aug 2025 — Present
Save Our Souls
Co-Founder & CTO

Built the native iOS (Swift) and Android (Kotlin) applications for a digital wellness platform. NFC-activated Devotion Mode on an offline-first architecture requiring no login or connectivity, with group infrastructure and shared analytics. Owned product and technical strategy through beta, including WCAG 2.1 compliance.

Feb 2025 — Jun 2025
Monograph
AI Automation Strategist

Built a prompt-driven sales toolkit that lifted conversion for the AEC SaaS team, and applied LLMs to lead qualification, call summarization, and CRM enrichment.

EARLIERCARVANA · CRUZ BUYS HOMES · ANODIZE CAPITAL · EDWARD JONES · C4 MOBILEB.S. FINANCE · ARIZONA STATE UNIVERSITY
(04)StackIN PRODUCTION USE
Data & Pipelines
Postgres · BigQuery · ETL and pipeline design · data warehousing · data-lake connectors · multi-tenant architecture · REST and webhook API design · Firebase
Integrations
HubSpot · Salesforce · Square · Zoom · Apollo · GoHighLevel · Slack API · custom REST and webhook
AI & LLM
OpenAI and Anthropic APIs · local inference (llama.cpp, GGUF, Metal) · RAG · evaluations · structured outputs · vision models · whisper.cpp · token and cost optimization
Agents
Autonomous agent loops · tool registries · MCP · Claude Code · Twilio, Deepgram and ElevenLabs voice pipelines
Languages
Python · Swift · Kotlin · TypeScript · SQL · Solidity
Web & Mobile
Next.js · React · SwiftUI · Kotlin · StoreKit 2 · RevenueCat · NFC
Cloud & Infra
Google Cloud (Architect-level) · Docker · Kubernetes · GitHub Actions · Vercel · Tailscale
Blockchain
Solidity · Foundry · Viem · Wagmi · Base/EVM · tokenomics · ZK attestations
Compliance
HIPAA-compliant system design · WCAG 2.1 accessibility · financial modeling
(05)How an engagement runs
01

Scope

A working session on what needs to exist and what it touches. You leave with an architecture and a build order, whether or not the engagement proceeds.

02

Build

Running software early and often — pipelines moving real data, agents making real calls. Progress is demonstrated, not reported.

03

Hand over

Into production with evaluations, cost controls, and approval gates where people belong. Documented so your team can own it, or I stay on retainer.

BUILT TO RUN
WITHOUT ME

Start an engagement →