We're building Driwego's web e-commerce platform — a marketplace for the Malaysian automotive aftermarket that was built for a specific kind of buyer and a specific kind of seller. This role is part of the team doing that.

One of the two Full Stack Developer positions we're filling carries an additional scope: owning the technical infrastructure that makes Driwego findable, measurable, and legible — to search engines, to ad platforms, to email systems, and eventually to AI. If you're a developer who has ever wanted to own the plumbing behind how a product gets discovered, not just how it works, this is that role.

RESPONSIBILITIES

1. Build and maintain the platform.

Our stack is TypeScript end-to-end: Medusa.js on the backend, Next.js on the frontend, PostgreSQL for data. You'll work across both sides as a normal part of delivering features.

2. Own features end-to-end.

From requirement to backend logic (Medusa modules, services, workflows, migrations), through the API layer, into the UI. You're not handed work in slices. You carry features through.

3. Own the technical marketing infrastructure.

This is the scope that distinguishes this role. You'll build and maintain the systems that make Driwego discoverable and measurable: SEO infrastructure, Google ecosystem integrations (Search Console, Merchant Center, Ads infrastructure), email infrastructure, and the foundations for AI context — structured data, schema markup, and the signals that help Driwego surface where buyers are already looking. This is not campaign management. It is the infrastructure that campaigns run on.

4. Initiate the AI marketing build.

This is new ground and we know it. The scope includes building the tools and agents that will eventually power how Driwego operates in an AI-assisted marketing environment — internal tooling first, then buyer-facing AI experiences as the platform matures and the data is there to support it. You'll build the infrastructure. What gets deployed against it is a product decision. Earn that conversation.

5. Use AI as a daily working tool.

Our team uses Claude as part of the day-to-day development loop. We expect you to be effective with AI-assisted workflows — and to know when to trust the output and when not to.

6. Translate vague requirements into working software.

Business stakeholders give direction at a high level. You'll join discussions to assess feasibility, push back where it makes sense, and shape ideas into something buildable.

7. Write clean, maintainable code.

Code that your teammates and your future self can read and extend. Sensible structure, sensible naming, sensible commits.

DAY-TO-DAY STACK

What you'll be writing almost every day:

What you'll touch depending on the feature:

QUALIFICATIONS

• 3+ years as a Full Stack Developer or in a similar end-to-end role.

• Strong TypeScript fundamentals. Comfortable with types, generics, and reading other people's TypeScript without guessing.

• Solid experience with Next.js (React.js) and a Node-based backend framework — Medusa.js, Express.js, NestJS, or similar.

• Comfortable with PostgreSQL through an ORM or query layer. Can write and run migrations, inspect tables through a GUI when debugging.

• Comfortable building forms with a schema-validated approach (React Hook Form + Zod, or equivalent).

• Comfortable styling with Tailwind CSS and component libraries built on Radix UI.

• Demonstrable understanding of SEO infrastructure — not theory, but actual implementation: structured data, Core Web Vitals, crawlability, canonical logic.

• Familiarity with Google's ecosystem for product discovery: Search Console, Merchant Center, or Ads tooling.

• Effective with AI-assisted development. You use AI for real work, not just autocomplete, and you can tell when its output is wrong.

• Strong written and verbal communication. Can explain a technical approach to teammates and non-technical stakeholders.

• Ability to research and problem-solve independently. We don't hand-hold.

Bonus: Experience with Docker, GitHub, Vercel, Redis, Elasticsearch, Sentry, or AI agent tooling (LangChain, LangGraph, or similar).

NICE-TO-HAVES

• Experience in a startup environment. Comfortable with self-direction, ambiguity, and incomplete specs.

• Experience with marketplace or two-sided platforms.

• Familiarity with the e-commerce domain: carts, checkout, promotions, fulfilment, returns.

• Experience building or deploying AI agents in a product context.

• Understanding of GEO (Generative Engine Optimisation) — how products and platforms surface in LLM-based discovery environments.