Placement rate is the number your program is judged on, and the AI engineering interview just changed under it. Roles now test RAG, agent orchestration, and LLM evaluation, not LeetCode, and LeetCode-prepped students are getting screened out of the highest-paid roles. Velocode is the first interview prep platform built for this shift. Now accepting founding partner applications for Fall 2026.
Career services teams are working with platforms designed for 2019 software engineering interviews. Meanwhile, your top students are interviewing for roles that didn't exist two years ago.
A Series B startup spent six months recruiting a Senior AI/ML Engineer from a FAANG company. Three weeks in, the CTO asked them to implement a basic data pipeline. The engineer couldn't do it. Not "did it poorly" — literally couldn't write the code.Read the full article →
The average fill time for AI roles dropped to 25 days because smart companies have figured out that a drawn-out process is the same as a rejection. If your interview timeline stretches past three weeks, you are almost certainly losing people to someone who moved faster.Read the full article →
We removed our coding and algorithms interviews and replaced them with an AI-native onsite. The role is shifting from building the machine to designing and honing it.Read the full article →
These aren't just industry articles — they're the conditions your engineering students are graduating into. Velocode is the response: the platform built specifically to prepare students for the AI engineering interview as it actually exists, not the LeetCode interview it used to be.
A complete AI engineering interview prep stack for your students, and an analytics dashboard for your career services team. Browse practice problems →
AI Engineer, ML Engineer, Data Engineer, AI Security Engineer, Software Engineer (AI-Era), and Forward Deployed Engineer. The full catalog, free for your students.
Every problem reported from a real interview at a verified AI company. No hypotheticals.
Students get scored on correctness, architecture, efficiency, and security — with the golden answer revealed after every submission.
Real-time analytics on student usage, score progression, and struggle areas. Outcome data you can share with your team and your dean.
Career services budgets get cut when they can't prove impact. Velocode turns student practice into data your team can act on and report up.
Placement rate is the number career services is judged on. Velocode gives you per-domain data on where your engineering students are interview-ready and where they're not, so you can show your dean exactly what's working ahead of recruiting season.
The students most at risk of a weak job search are the ones quietly falling behind on technical prep. Velocode's struggle-area analytics let your team spot and support them before recruiting season, not after.
As institutions add AI-readiness to how they report student outcomes, Velocode gives you concrete numbers: which students are training on AI engineering, in which domains, and how their scores are progressing over time.
Your dean wants outcomes, not activities. Your dashboard gives you both — broken down by domain, by cohort, and by individual student where it matters.
SAMPLE100 at checkoutWe work with 2-3 founding partner schools per semester to ensure white-glove support. Onboarding is fast and the lift on your team is minimal.
Reach out to discuss your school's needs. We work with 2-3 founding partner schools per semester to ensure white-glove support.
We set up a custom dashboard for your team and an SSO flow for your students. Your career services team gets a dedicated contact.
Send the invitation email to your students. Track usage, scores, and struggle areas in real time. We run one workshop per semester for your students.
If anything else comes up, the inquiry form below goes to a real human on our team.
We work with 2-3 founding partner schools per semester. Tell us a bit about your program and we'll send a tailored proposal.