// The difference
Most developers who can build this have never worked a support queue, fought chargebacks, or managed an entire backend process. I've done all of it.
For over a decade I worked the front line of customer and technical support, then ran e-commerce customer service, fulfillment, and PayPal/Shopify disputes by hand, and managed the whole backend process end to end, long before I automated any of it. That's why what I build fits how a store actually operates, not how a developer imagines it does.
// What I build
For a DTC e-commerce brand, I designed and built a multi-agent system that runs the back office unattended, every day:
Catches stuck orders
Flags late or stuck shipments and follows up with suppliers automatically, before the customer has to ask.
Checks every order
Screens each order for fraud signals before it ships, so the risky ones get held instead of charged back later.
Replies that learn
Drafts customer-service replies that get sharper each time a human edits one. The team stays in the loop, the queue gets faster.
Never misses a deadline
Tracks PayPal and Shopify disputes end-to-end so a response window never lapses unanswered.
Straight to Slack
A daily P&L report compiled automatically and posted to Slack each morning. No one has to pull it together by hand.
The difference between automation that helps and automation that starts fires: mine wouldn't double-charge or double-email a customer if a step retried, it alerted the moment something failed, and it stayed cheap to run as volume grew.
Built and run in production for a live DTC brand.
// Stack
AI / LLM
Automation & Dev
E-commerce & Payments
CRM, Support & Messaging
Collaboration & Ops
// Capabilities
Automation & Dev
Production automation that runs unattended: idempotent, self-monitoring, and cheap to scale; it won't double-charge and it alerts the moment a step fails.
AI / LLM
LLM agents that draft, screen, and decide, and sharpen with every human edit, keeping a person in the loop while the queue speeds up.
E-commerce & Payments
The back office run end to end: orders, fulfillment, fraud screening, and chargebacks won across multiple processors and currencies.
Leadership
Built and led remote teams, from a 15-person CS unit to a 70+ person operation, with hiring, coaching, and process that scales.
CRM & Support
A chaotic support inbox turned into a fast, measured queue: SOPs, QA, and escalation paths that hold up at volume.
Collaboration & Ops
Distributed teams kept aligned: clear docs, tracked work, and the daily reporting leaders actually read.
// Experience
- Design and build custom Python + Claude automation that runs e-commerce back offices unattended: order monitoring, fraud screening, AI-drafted support, dispute tracking, and daily reporting.
- Ran the full back office as Operations Manager for a couple of DTC brands, leading the team leaders across customer service, creative, copywriting, ads, fulfillment, and order management: 70+ remote staff. Built and led a 15-person CS team before scaling up to the whole operation.
- Owned customer service, fulfillment, and PayPal/Shopify dispute handling end-to-end, winning 80%+ of the disputes I represented.
- Wired the brand's systems into one reliable, self-monitoring operation. It alerted the moment a step failed instead of breaking silently.
Earlier: BPO / customer & technical support · 2006–2017
// Education & certifications
Education
Certifications
- Project Manager: Role & Skills · Metropolitan School of Business & Management UK, 2022
- Tech Lab Certification · Dell Int'l Services
// Contact
Tell me where the manual work is. I'll show you what I'd automate first.