AI-First Engineering Intern

For more information, visit xsolla.com.

Why This Role Exists

Xsolla is going all-in on becoming an AI-first company, and we're not waiting for a slow rollout to get there. We're offering AI Engineer Internships in regions across the globe to help drive that shift directly, not by sitting in the back office, but by building.

You'll work on two things:

1. Internal AI initiatives – helping unlock AI tooling and integrations across Xsolla faster than our existing teams can alone.

2. Proof-of-concept builds on our own APIs – showing our product and engineering teams what's possible when you build with AI as a core part of your workflow, not an afterthought.

This isn't a shadow-and-observe internship. You'll ship code that goes to customers – internal teams or external players and game developers – working closely with senior engineers and fellow interns across our global regions.

Who You'll Work With

You won't be isolated on an intern-only project island. You'll work closely with senior engineers who are actively rebuilding how we write software, and you'll be part of a global cohort of interns building in parallel across our regions. That combination is the point: senior engineers give you a bar for what production-grade, customer-facing code looks like, and your fellow interns give you a peer group to trade ideas, code, and AI workflows every week.

What You'll Do

• Partner and collaborate with senior engineers to identify where AI tooling and integrations can remove friction, and build the fix.

• Build applications and integrations on top of Xsolla's APIs and SDKs that show internal teams how to move faster using AI-assisted development.

• Ship work that matters. What you build is expected to reach real users – whether that's an internal tool an engineering team adopts or a customer-facing integration – not a throwaway exercise that gets shelved after your internship ends.

• Use agentic coding tools (Claude Code, Cursor, or similar) as your default way of working – not a novelty you reach for occasionally.

• Share what you build. We run weekly 30-second lightning-talk demos where everyone shows how they used AI to solve something that week – you'll be expected to bring something real.

• Work with minimal process. You'll get context, a problem, and a mentor – the rest is on you to figure out and build.

• Learn from and collaborate with both directions: senior engineers who'll mentor you on production-grade practices, and fellow interns across markets you'll trade ideas and code with at the weekly demos.

What We're Looking For

You build things because you want to, and that you already use AI to do it faster.

• Genuine passion for building. You have side projects, hackathon entries, open-source contributions, or something you shipped just because you were curious. You didn't need an assignment to make it happen.

• Real AI fluency. You've actually used tools like Claude Code, Cursor, Copilot, or similar agentic coding tools to build something – not just asked ChatGPT to explain a concept. You should be able to explain how you used AI to get there and how you confirmed it actually worked – not someone who fires off a prompt and hopes for the best.

• Bias toward action. Given an ambiguous problem, you start building before you ask for a spec.

• Comfort with developing modern full-stack solutions – we care more about how fast you learn than what you already know cold.

• Open to current undergraduate students, graduate students, and recent graduates of a Computer Science, Software Engineering, or related program. If you're pursuing a graduate degree and don't mind taking on an internship-level role to get hands-on with AI, we want to hear from you.

How to Apply

No take-home assignments, no formal problem sets. We're evaluating proof of work, not your ability to complete an assigned exercise. Please include:

1. A link to a GitHub profile, deployed project, or anything else you've built – the more recent and self-directed, the better.

2. A short answer (2-3 sentences, or a 2-minute video/Loom if you'd rather show than tell) to: “What's something hard you built recently, and why did you build it?”

We're not grading for correctness or polish. We're looking for whether you have a real answer, and whether it's clear you actually did the work yourself (with AI as your tool, not your ghostwriter).