Product Engineering Intern

About GoStudio

GoStudio.ai is the one-click AI studio for people, pets and products. Hundreds of use-case apps and image and video templates let anyone create, recreate or edit a photo or video in one click, with no prompts.

We're a bootstrapped team of eight in Bengaluru. Our founder, Kanika, started GoStudio solo from a tier-3 Indian city. Neeraj, who has built Practo, Quikr and CommonFloor before, now works with Kanika full-time as a mentor to build the product.

We take freshers seriously: the people leading our work today joined as freshers just a year ago. We hire for what you've made and how you think, not your CV. We're a profitable startup with no VC funding, building a small, close team where everyone owns the product. So we're looking for someone who wants to stay for the long term.

The role

You'll own part of GoStudio's product end to end: why we build it, how it's designed, how it ships and how it performs. Your first big area is helping us build an AI agent that creates and edits images, videos and audio, and working out which AI models actually solve our customers' problems.

This is a product engineering role, not a machine learning role. You won't train models. You'll think like a product manager (what is the user trying to get done, and which metric tells us we helped?) and like a system architect (what's the right design, what does it cost, what breaks, how does it scale?). New models launch every week, so you'll also decide which ones deserve our attention and which are noise.

AI writes much of the code, and you'll use it to move fast. You own what ships: you read it, test it, explain it, run it, watch how it performs and fix it. You'll start with a scoped area, a mentor and a real task, work directly with the founder, and take on more as you show judgment. Your work goes to production.

What you'll do

You'll start in one of these areas and may touch the others:

• Start with why. Before you build, write a short note: the user problem, the metric it should move, and the design you chose and why. We review it together, then you build. Keep these notes so the team can reuse them.

• Help build the agent. Work on an agent that takes a request, picks the right steps and tools, and produces or edits an image, video or audio file. You’ll help design how it plans, calls models, checks its own results and handles failures.

• Make architecture choices. Decide how a feature should work: the data flow, the cost per result, what happens when a model is slow, fails or changes, and how it holds up as more people use it. To do this well, you need to understand the systems we use (AI models, APIs, queues, storage, databases) and the trade-offs between them: why one option fits a job better than another on cost, speed, quality, reliability and effort to maintain.

• Evaluate models against real use cases. Take a customer job, such as making a product photo look like a studio shot, and test candidate models and prompts on it. Judge the results on quality, cost, speed and reliability, then recommend which to use.

• Do it. Do it right. Do it better. That's how we build. You'll run new engineering and marketing systems by hand first, until you understand them well. Then you'll automate them with AI: checks, reports, alerts and repetitive work that run without you. You'll keep reviewing the systems we have and find the ones worth optimising next.

Who you are

• Think like a product owner. You ask why before how: who is this for, what are they trying to get done, and which number tells us it worked? After launch, you watch that number.

• Build like an architect. You see how the parts connect (the user, the model, the tools, the cost) and what happens when one fails or usage grows. You can explain the trade-off behind a design.

• Critical thinking. You question assumptions, check the evidence and reason your way to a decision, instead of going with the first answer you hear. This matters more now that AI gives confident answers in seconds: your job is to judge them.

• Problem solving. It’s your nature. At home, with friends or at work, you notice what isn’t working and enjoy finding out why and fixing it, without being asked.

• Learning & hands-on. You’ve built something real (an app, an AI workflow, a bot), and you use AI to code while checking its work. You follow what’s new in AI and can tell what matters from hype. You say what you don’t know and you take feedback well.

What you get

• Real ownership. Your project goes live, and you see its impact on real users.

• The latest technology. You’ll work with agents, MCP, APIs, web, mobile apps, browser extensions and more.

• A pre-placement offer (PPO) for interns who do strong work.

• Room to grow. Your mentor helps you find your strengths and guides you toward the right career path.

How we hire

Three steps, and we tell you everything upfront. We reply at every step within 48 hours.

1. 1

   Apply~20 min

   The form below: your GitHub or portfolio link and a few questions. AI help is fine. We read for how specific and honest your answers are.

2. 2

   Practical assignment~1 day, within 72 hours

   We send you a small product brief. You build a working web app, deploy it to a live URL, and send us the link, the code and a one-page note: why you built it this way, the architecture, what you’d measure and how it would scale. You can use AI tools. We care that you finish and that you understand what you built.

3. 3

   In-person interview at our Indiranagar, Bengaluru office~3 hours

   Walk us through your app and answer questions about your choices, the product and how it would work at scale. You'll also do a short live task on your own laptop (AI allowed) so we can see how you work.