AI-Powered Full Stack Engineer (Agentic & Web)

【What You'll Do】

You'll be part of a very direct loop:

Turning user intent into product value—and potentially revenue.

Your day-to-day will include:

1️⃣ Product Development (End-to-End Ownership)

• Design and build backend services (Go / Python)

• Develop OpenAPI-first APIs (evolving toward AI / agent interfaces)

• Build frontend experiences (Vue / Nuxt), including AI Q&A, interactive flows, and embedded content

2️⃣ AI Integration (Production, not PoC)

• Integrate LLMs / AI models into real product features

• Apply them to use cases such as content understanding, question generation, recommendation, and conversational flows

• Work with real users and real traffic—not just demos

3️⃣ Rapid Experimentation & Iteration

• Build prototypes quickly (in days, not weeks)

• Decide what to push forward and what to stop

• Continuously move strong ideas into production

4️⃣ Full Ownership (From Development to Production)

• Deploy, monitor, and operate the systems you build (Kubernetes / EKS)

• Use tools like Prometheus, Grafana, and Sentry for observability

• Diagnose and resolve issues quickly when they occur

5️⃣ Engineering × Business Thinking

• Understand how the product creates value (e.g., conversion, matching, traffic quality)

• Consider performance, user experience, and cost (FinOps) in technical decisions

6️⃣ AI-Native Development Workflow

• Use AI tools (Claude, Cursor, etc.) as part of your daily workflow

• Automate testing, documentation, and development processes

• Continuously improve development speed and quality

【Requirements】

• 3+ years of full-stack or related development experience (aligned with the stack above)

• Experience building and shipping products end-to-end (frontend, backend, deployment, operations)

• Proficiency in Go or Python (at least one), and Vue.js or similar frontend frameworks

• Hands-on experience applying AI / LLMs in real product scenarios (not just experimentation)

• Ability to move forward in ambiguous situations instead of waiting for perfect clarity

【Nice to Have】

• Familiarity with agent architectures or tools (MCP, LangGraph, n8n, etc.)

• Experience in ad tech / martech / SaaS

• Understanding of basic business metrics (e.g., conversion rate, traffic value)

【How We Build (Please Read)】

We've documented how we actually build products, including:

• How we ship AI pipelines within a day

• How AI tools become our default workflow

• Why everyone here is a Product Builder—not just an engineer

→ https://careers.mlytics.com/how-we-ship.html

We know it's not a short read.

But if you take the time to go through it—and even come to the interview with your thoughts or questions—it will significantly increase the chances of a strong match.

【Final Note】

If you've read through How We Build and found parts you strongly agree with or even disagree with—we'd love to hear your perspective in the interview.