Description
Ready to compress years of AI learning into one summer?
The Alpha AI Engineering Internship is where Stanford, MIT, and UT’s sharpest freshmen and sophomores turn raw potential into world-class skill. This isn’t a padded résumé line; it’s a high-intensity launchpad for the next generation of AI-first builders.
For 8 weeks in Austin, you’ll push beyond classroom theory and into founder-speed reps, expert feedback loops, and applied engineering challenges that demand your best work. You’ll learn to build with AI at a level that puts you years ahead of your peers, while gaining the kind of tangible outputs, mentorship, and network that open doors for life.
This program is designed for the few who want to go faster, learn harder, and stand taller than the crowd. If you’re serious about leading in AI, this is your other half of education.
Logistics:
- Duration: 8 weeks, June 22 – August 14, 2026
- Location: Austin, TX (the only place where tacos, tunes, and tech collide!)
- Compensation: $20,000 + expenses
- Application Period: Rolling, now open for submissions!
- Who we’re looking for: Freshmen or sophomores at MIT, Stanford, or UT; must have experience with and passion for coding, machine learning, and AI; eager to learn fast and work hard
Selection is merit-based and fast: apply, complete a timed cognitive assessment, a coding assessment, and talk to the team. Offers follow quickly for top performers.
If you’re ready to supercharge your future with an unparalleled summer internship, apply now. Spots are limited.
What you will be doing
- Build and deploy AI-first projects across frontend, backend, and agentic systems using tools like Cursor, LangChain, and Claude Code.
- Apply advanced generative AI techniques—prompt engineering, RAG, multimodal models, and LLM optimization—to real-world problems.
- Collaborate with elite founders, CTOs, and AI pioneers, receiving hands-on mentorship and rapid feedback loops.
- Deliver measurable outcomes that demonstrate pace, product thinking, and engineering quality at startup speed.
What you will NOT be doing
- Writing CRUD apps or patching legacy systems—your work will be AI-first, not yesterday’s software.
- Sitting in long meetings or handling busywork; every task will be designed for impact, not routine.
- Following scripted tutorials or shipping demo-ware; your projects will have real-world value.
- Competing against peers; this is about collaboration and collective excellence, not internal rivalries.
Key responsibilities
Deliver AI-powered projects with tangible business outcomes while accelerating your technical and professional growth at elite speed.
Candidate requirements
- MIT, Stanford or UT undergrads only; freshman or sophomore standing during Summer 2026 (anticipated graduation 2028–2029).
- Exposure to coding and AI through coursework, projects, or shipped work.
- Able to pass a timed coding assessment.
- Willing to relocate to Austin, TX for eight weeks; full-time, on-site.
- High agency, fast learner, clear communicator, strong work ethic.
Applying for a role? Here’s what to expect.
Crossover's skill assessment process combines innovative AI power with decades of human research, to take the guesswork, human bias, and pointless filters out of recruiting high-performing teams.
Chat-style
screening interview.
Cognitive 
aptitude test.
Prove real-world 
job skills.
Interview with the hiring manager.
Accept Job Offer.
Pass 
proctored test.
Frequently asked questions
About the role
Reviews
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Recruitment sucks. So we’re fixing it.
The Olympics of work
It’s super hard to qualify—extreme quality standards ensure every single team member is at the top of their game.
Premium pay for premium talent
Over 50% of new hires double or triple their previous pay. Why? Because that’s what the best person in the world is worth.
Shortlist by skills, not bias
We don’t care where you went to school, what color your hair is, or whether we can pronounce your name. Just prove you’ve got the skills.
Join the world's largest community of 
AI-first remote workers.