Product Engineer (High Autonomy / AI-Native)

We are looking for a

Product Engineer

who combines the speed of an "AI-native" workflow with the rigor of a Principal Architect.

We believe the future of software belongs to engineers who use LLMs (Cursor, Claude, Copilot) to accelerate development by 10x—but who possess the deep Computer Science fundamentals to know exactly what is happening under the hood.

You will not just be "coding"; you will be owning product verticals end-to-end. You will act as the

Editor-in-Chief

of the codebase, using AI to generate velocity while applying your deep technical expertise to ensure security, scalability, and maintainability.

The "Vibe Coding" Filter If you rely on AI because you don't know how to write the code yourself, this role is not for you. If you use AI to automate the tedious parts so you can focus on complex architecture and business logic, we want to talk to you.

What You Will Do

End-to-End Ownership:

Take features from a rough idea -> technical spec -> rapid prototype -> production-grade deployment. You own the outcome, not just the ticket. Architectural Rigor:

Design robust data models, API schemas, and system architectures. You will make the high-stakes decisions on state management, database locking strategies, and latency trade-offs that an LLM cannot verify. AI-Accelerated Development:

Utilize modern tooling (Cursor/Windsurf, V0, Copilot) to skip boilerplate and ship at startup speed. The "Quality Gate":

You are responsible for auditing AI-generated code. You must be able to spot subtle hallucinations, security vulnerabilities (IDOR, XSS, Injection), and O(n²) loops that the AI missed. Debug the Depths:

When things break (and they will), you have the deep Linux/Networking/Runtime knowledge to debug issues that "regenerating the prompt" won't fix.

What We Are Looking For

Deep CS Fundamentals:

You have a strong grasp of data structures, algorithms, concurrency, and memory management. You understand why the code works. Production Experience:

4+ years of shipping software. You know the difference between code that runs in a notebook and code that survives 10k concurrent users. System Design:

You can discuss the trade-offs between SQL vs. NoSQL, Monolith vs. Microservices, and REST vs. gRPC without needing to Google it. Product Instinct:

You care about the user experience. You don't wait for a pixel-perfect design; you have the intuition to fill in the gaps and make product decisions. The "Builder" Mindset:

You treat the AI as a junior developer who reports to you. You delegate the typing, but you own the logic.