Product Engineer

Company: Canvas (canvasx.ai)

Location: Remote

Experience: 1–3 Years or more

Compensation: INR 15–20 LPA + ESOPs

Please note that failure to submit the required assignment mentioned in the application form will result in the rejection of your application.

We're Canvas — a research and R&D lab building AI products. We started the day ChatGPT launched and have shipped more than 15 AI products since. Right now we're building Getsketch.ai, and that's where this role plugs in.

You'll work directly with our CEO and CTO, shaping the AI products we're building: Sketch and the next ones in the pipeline. Small team, fast loop, real product decisions in the room with you.

You'll own pipelines end-to-end, and the product calls that go with them. The brief might be one line in Slack. Your job is to figure out what to build, build it, ship it, then watch how people use it.

We're a startup, and we need a product engineer. Someone who can hold the spec in their head and the code in their hands at the same time. If you want a PM to hand you tickets, this isn't the role. If you'd rather specialize deep in one slice of the stack, it isn't either.

Find the Edge: Notice what's missing or broken in our products. Propose features, prototype them in a weekend, ship the ones that earn their keep.

Make the Call: When a spec is ambiguous, you decide. Talk to users, look at the data, and make the product call. We'll back you.

Build the Interface: Develop responsive, interactive UIs in Next.js, React, and Tailwind that real customers depend on.

Power the Backend: Build and maintain Node.js + Fastify services that connect frontend to data and intelligence.

Plug in the AI: Integrate LLM services — OpenAI, Claude, Gemini — to make conversational features feel natural.

Write for the Long Run: Clean, maintainable, well-tested code across the stack. Code another engineer can pick up six months later without a tour guide.

Frontend: Next.js, React, TypeScript, Tailwind

Backend: Node.js, Fastify, REST/LLM APIs, MongoDB

DevOps: Docker, AWS (Lambda, ECS), GitHub

The Experience: 1–3 years building products end-to-end. Personal projects count if you actually shipped them.

The Foundation: Strong JavaScript/TypeScript, HTML/CSS, and modern JS frameworks.

The Backend Side: Comfortable with backend development and working with APIs.

The Taste: You notice when a product is bad. At the click, the copy, the empty state. You have opinions about what makes software feel good.

The Curiosity: Genuine interest in AI technologies and what LLMs can actually do (and what they can't).

The Craft: Sharp attention to detail, willingness to learn, and ownership over what you ship.

1. Application: Fill out our application form with your details.
2. The Assignment: Complete the assignment shared in the form (7 days to submit). The deliverable is a short technical note, not code. Applications submitted without the technical note will not be considered.
3. Note Review: We review your technical note for thinking, structure, and craft.
4. Final Conversation: A discussion with the team to walk through your note, your process, and mutual fit.

Your code ships into real AI products customers use, not internal experiments.

Work closely with the CEO and CTO. Your decisions shape the product. Propose a feature in standup, ship it by Friday.

Learn the craft of building production AI tools end-to-end, from LLM integration to deployment.

Competitive compensation with meaningful ESOPs — real skin in the game.