AI Workflow Design · Governance · Automation

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I design governance frameworks, build QA tooling, and automate workflows that help teams use AI reliably. The industry changes. The approach does not.

See the work What I Do Download Resume
Stanley Carter
6,704
SKUs through governed pipeline
16,146
SKUs audited via automation
5,000
LLM conversations reviewed
3%
Post-calibration reviewer variance

Core Expertise

What I Do

LLM & AI Governance

Turning raw AI output into structured, brand-safe, auditable content, at scale.

  • Zero-Drift CalibrationBuilt scoring systems that cut inter-reviewer variance to under 3% across 50+ person teams.
  • Prompt EngineeringGoverned prompt pipelines that deliver brand-compliant output from any model, every time.
  • Evaluation FrameworksAutomated LLM scoring benchmarked against real enterprise KPIs, not vibes.
Workflow Automation

If someone on your team is doing it manually, I'm building the system to do it automatically.

  • API & Webhook IntegrationEvent-driven pipelines in Python and n8n, triggered by uploads, not humans.
  • Human-in-the-Loop Design95% automated. Edge cases route to the right person instantly, with full context.
  • Agentic OrchestrationMulti-agent AI systems that execute complex, multi-step business logic, no babysitting.
Scalable Data Pipelines

From 117 SKUs processed by hand to 16,000+ governed by code.

  • Catalog EngineeringIngest, clean, and govern hundreds of thousands of e-commerce data points without breaking a sweat.
  • Automated ComplianceAnomaly detection that flags bad data before it ever touches production.
  • Pipeline ModernizationReplace fragile spreadsheets with cloud-native, zero-maintenance data workflows.

Social Proof

What managers say.

"

Stanley quickly demonstrated strong technical curiosity and a clear passion for using AI to drive operational efficiency. He brought thoughtful ideas around automation and AI governance, and then actually built the tools to prove it.

Courtney Grisham
Director of Ecommerce · Shoe Station
"

In the AI space, data quality is everything. Stanley engineered the exact calibration guardrails we needed to bring reviewer variance down to negligible levels. His work directly improved the reliability of our core datasets.

Stephani J. Brito
Growth Program Manager · Scale AI

Case Studies

Seven projects. All real.

Automated asset verification results
Python · Automation

Amplience Photo Audit

Automated photo verification across 16,000+ products. What used to take hours now runs in one command.

16K+
SKUs audited
→
 AI Governance before and after
AI Governance · Workflow

AI Content Governance System

9 documents that replaced ad hoc AI use with a consistent, auditable standard. Works across any model.

15→<1
Days turnaround
→
 GA4 tracking dashboard
SEO Copy · GA4 · Tracking

Brand & PLP SEO Copy Program

24 pages written and tracked across two retail banners. Built the measurement system to go with it.

24
Pages authored
→
 Automated URL QA console
Python · QA Tool

Python Brand Page QA Tool

~2,000 brand URLs checked across both banners. Found 20 missing pages. Improved across two versions.

~2K
URLs audited
→
 LLM output before governance
LLM Evaluation · QA Management

LLM Evaluation at Scale AI

Final-line quality decisions on 5,000+ AI conversations. Grew from freelance contributor to QA Manager in under a year by reducing reviewer variance across a rotating team to under 3%.

<3%
Post-calibration reviewer variance
→
 PDP Pipeline output
Python · Claude Vision API

PDP Automation Pipeline

From label photo to production-ready product copy in 40 minutes. A vision pipeline that replaced 8+ hours of manual work with a single button click. Processes full batches unattended.

117
Unique styles, 1 run
→
 n8n workflow diagram
n8n · Workflow Automation

Footwear PDP Generator via n8n

The Python pipeline rebuilt for the cloud. Drop photos into Google Drive, get governed product descriptions delivered to your inbox. No local machine, no terminal, no one watching it run. Config and prompts controlled from a Google Sheet.

0
Lines of code to operate
→

About

Built on retail.
Trained on AI.

I started in retail, selling, troubleshooting, and managing stores. Each role taught me something about systems: how they break, why they slow down, and what happens when nobody builds the guardrails.

At Scale AI I evaluated thousands of LLM outputs against production standards. That became the foundation for what I build now: governance frameworks, QA tooling, and workflows designed to catch problems at creation, not at review.

LLM Quality Ops
Evaluation rubrics, acceptance criteria, calibration, variance reduction
AI Governance
Framework design, cross-functional adoption, change management
Operations
Workflow design, sprint delivery, QA checkpoints, stakeholder coordination
Tools
Python, Excel, GA4, SQL, Oracle Fusion, Claude, ChatGPT, openpyxl
LocationRock Hill, SC (Open to Remote)
RoleeCommerce Content Specialist
CompanyShoe Carnival, Inc.
EducationB.S. Marketing, SNHU 2024
CertificationsHubSpot SEO · Digital Marketing · Social Media
StatusOpen to Roles
GitHubgithub.com/MNG-AI
LinkedInlinkedin.com/in/stanley-carter-jr
Emailskcart79@gmail.com