Graduate AI Solutions Engineer.

The work

From an idea to something testable.

In a future project, you could contribute to:

• Breaking a business problem down into a clear workflow, inputs and expected outputs.
• Designing and refining prompts for large language models, with examples and clear constraints.
• Building small AI-assisted applications, automations and integrations with code and APIs.
• Checking AI responses and generated code: finding errors, comparing approaches and recording what improves.
• Helping connect prototypes to existing software and deploy them to a suitable cloud service.
• Explaining your approach, documenting decisions and working feedback in.

Essential foundations

Potential over years of experience.

• A recent degree from Istanbul Technical University (İTÜ), particularly Mathematics Engineering or Computer Engineering.
• English good enough to read technical documentation, write clear notes and discuss your approach.
• Basic programming and software reasoning: you can read and adapt a small piece of code in at least one language.
• A basic understanding of how an application, an API and a database work together. You don't need to be an expert in all three.
• Interest in generative AI and a habit of checking an answer instead of assuming it is correct.
• Willingness to learn unfamiliar tools, ask useful questions and follow through on a small task.

No professional experience or previous internship is required. Coursework and self-directed learning count.

Nice to have — not a checklist

Show us what you have explored.

• A course project, graduation project, hackathon entry or personal experiment you can explain, including your own part in it.
• Some Python or JavaScript/TypeScript, Git, JSON or HTTP APIs.
• Trying a cloud or deployment platform such as Azure, AWS, Google Cloud, Vercel, Firebase or Supabase.
• Trying AI assistants, AI coding tools or workflow automation, and knowing where they fail.
• A GitHub repository, short demo, write-up or portfolio. A public portfolio is optional.

You don't need to know every tool listed here, train your own model or have production deployment experience.

Getting to know each other

Explain how you think.

1. 1Introduce yourself: a CV if you have one, your degree details and a short note using the prompts below.
2. 2Talk through your approach: selected candidates discuss a project or learning exercise, with a short conversation in English.
3. 3Explore a small example: a brief fictional problem, worked through together. AI tools are welcome; we want to know what you checked and why. This is never unpaid client work.
4. 4Reconnect when there is a fit: we contact relevant candidates when a funded project creates a suitable role.