Senior Product Engineer

Our Client is hunting for its next product engineer , someone who has a strong desire to build, smart enough to untangle gnarly problems fast, and bold enough to ship data-powered retail features that move the revenue needle today .

They're scaling from 12 to 50 stores, spinning up a headless commerce stack (MedusaJS + AWS), and launching our first customer-facing app. If you want to own big chunks of that journey and write the playbook for modern, AI-assisted development in African retail read on.

About Our Client

They buy overrun, overstock and returned apparel from Europe’s biggest fashion houses, revive it, and give it a second life in emerging markets.

Their mission : To be the world’s most innovative fashion outlet

Physical footprint : 12 stores (SA) 20 stores by year-end

Tech footprint : AWS-native, React, Next.JS, React Native, TypeScript, Python, MedusaJS

Data obsession : They’re building a real-time lake, ML-powered buying tools, and an offline-first POS because smarter data = better buying = more sales .

Role Overview

You’ll own features end-to-end  from first sketch to metrics dashboards while leaning heavily on AI coding copilots and tools to keep velocity extreme and busy-work minimal.

What You’ll Do

AI-Native Development

Context Engineering

Develop, orchestrate and refine AI agents for boilerplate and tests.

Drop into “manual mode” with serious engineering firepower when the bots tap out.

• Share prompt and context-engineering tricks and workflows with the team.

Become an AI-enabled weapon!

Product Engineering & Ownership

Define success metrics, instrument them, and iterate fast.

Pair with product & design on continuous discovery (we interview store staff and customers weekly).

Composable Commerce & Integrations

Keep everything observable (OpenTelemetry traces, k6 smoke tests).

Customer & Stakeholder Loop

What We Offer

Who Thrives Here

You’ve shipped real products and improved them post-launch.

Complexity excites you, integrations, inventory math, syncing offline data.

You treat AI tools as teammates, not magic.

“Good enough to ship” beats “perfect later,” but you refactor ruthlessly.

If this sounds equal parts thrilling and terrifying, you’re probably our kind of engineer.