Crack the 2026 AI Interview: AI Engineer, Applied AI and FDE

Dr. Aki Wijesundara

PhD in ML | Google AI Accelerator Alum

Manu Jayawardana

Exited AI Founder | Founder, TAI Labs

Pass the AI interviews companies actually run in 2026, from screen to offer.

You're prepping with 2023 material for 2026 interviews.

Meta and Google now run AI-assisted coding rounds where the interviewer reads your entire AI conversation. FDE hiring is up over 1,000%, and most openings aren't at the labs, they're at startups, enterprise SaaS, and consultancies.

Grinding LeetCode alone won't get you through these interviews.

In 4 weeks, you'll prepare for the interview loops companies actually run, whether you're targeting AI Engineer, Applied AI or Forward Deployed roles.

Practice the AI-assisted coding format used in modern technical interviews, before it counts
Drill the Python patterns and problem-solving skills that show up in real AI engineering loops
Design RAG and agent systems the way interviewers evaluate them
Run the FDE case study, then learn how to negotiate the offer properly

Our students come from MAANG companies, and some have landed roles at MAANG straight after finishing the bootcamp.

Want to see how we teach first? Watch our free recorded mini-series, Think Like an AI Engineer.

A limited number of need-based scholarships are available for applicants facing real financial hardship. See if you qualify.

What you’ll learn

Leave with a repeatable system for selling and persuading in every context you actually face.

Practice the 60-minute multi-file format with an AI panel, where the interviewer reads your full prompt history
Score yourself on the four signals graded: decomposition, verification, code reading, communication
The mindset shift that makes every conversation more persuasive

Recognize the six pattern families that recur in AI company loops within ten seconds
Handle layered Python builds: rate limiters and LRU caches, then make them concurrent

Take RAG and agent designs from requirements to architecture in 45 minutes
Name failure modes, design eval harnesses, and budget cost with prompt caching and model routing

Decompose ambiguous customer briefs with a repeatable structure: clarify, prioritise, propose, name risks
Handle customer scenarios and build-under-pressure demo rounds

Map frontier labs, AI-native startups, and enterprise loops, and match your evidence to each bar
Build the 3 portfolio projects that pass screens: RAG with citations, an agent with guardrails, an eval harness

Prepare behavioral stories for every tier, including the stalled-deployment story FDE interviewers ask for
Anchor on total comp, move first on equity, and run parallel processes to create competing offers

Learn directly from Aki & Manu

Dr. Aki Wijesundara

Contact

AI Founder | Educator | Google AI Accelerator Alum

Manu Jayawardana

Contact

AI Advisor | Founder, TAI Labs

Previous Students from

See all products from TAI Labs

Who this course is for

The AI Engineer candidate.
The FDE aspirant
The career switcher

Prerequisites

Working Python and basic coding ability
You can write and debug Python. We sharpen it for interviews, we don't teach it from zero
Some exposure to LLM tools or products
You've used or built with AI tools. Production experience helps but isn't required.

What's included

Live sessions

Learn directly from Dr. Aki Wijesundara & Manu Jayawardana in a real-time, interactive format.

4 live deep dives

Four 90-minute sessions covering coding formats, patterns and Python, AI system design, and the FDE rounds

Weekly live office hours

Bring your CV, portfolio, or an upcoming loop and work through it live every week

Personal CV and portfolio feedback

Submit your CV and one project in week 1 and get direct feedback on both

Mock interview reps

Timed design mocks, decomposition reps, and AI-assisted coding practice, all scored against real rubrics

Lifetime access to recordings

All sessions recorded. Revisit them before every interview loop you run

Certificate of completion

Share it on LinkedIn once you finish the course

Community of AI candidates

Compare loops, share referrals, and find mock interview partners

Maven Guarantee

Your purchase is backed by the Maven Guarantee.

Course syllabus

8 live sessions • 5 lessons • 4 projects

Week 1

Aug 25—Aug 30

How AI interviews work in 2026, and how to land one

1 item

Aug

Session 1

Tue 8/253:00 PM—4:30 PM (UTC)

Aug

School Office Hours

Tue 8/259:00 PM—10:00 PM (UTC)

Optional

Assignment 1

1 item

Week 2

Aug 31—Sep 6

Week 2 — LeetCode patterns and the Python round

1 item

Sep

Session 2

Tue 9/13:00 PM—4:30 PM (UTC)

Sep

School Office Hours

Tue 9/19:00 PM—10:00 PM (UTC)

Optional

Assignment 2

1 item

Free resources

Schedule

Live sessions

2 hrs / week

One 90-minute deep dive each week covering that week's round, taught with real reported questions from 2026 loops and ending with a concrete prep assignment

Tue, Aug 25
3:00 PM—4:30 PM (UTC)
Tue, Aug 25
9:00 PM—10:00 PM (UTC)
Tue, Sep 1
3:00 PM—4:30 PM (UTC)

Projects

2 hrs / week

Weekly homework mirrors real rounds: timed problems in your own AI-assisted setup, recorded decomposition reps, and a small RAG or agent build with evals.

Lifetime Access to All Recordings, Materials and Async content

5 hrs / week

Revisit the materials and lectures anytime. Recordings and slides are made available to all students. Learn in your own time & get a tonne of support in live sessions and homework huddles.

Testimonials

The AI training approach is outstanding. Our team learned to build practical AI solutions that we could implement immediately in our educational platform. The hands-on methodology made complex AI concepts accessible to our entire development team.
Kavi T.
CEO of Tilli Kids / Stanford PhD
Not only are the instructors experts in their field, they're incredibly skilled at breaking down complicated AI concepts so students can grasp them quickly. Anyone interested in building foundational AI knowledge should take this training - it's worth the investment.
Dr. Elizabeth Creighton
Founder & Principal at Brazen
The instructors help break down AI model development and clearly have plenty of experience to help others learn about complex concepts like infrastructure setup. The practical approach to NLP and LLM applications was exactly what our team needed.
Alissa Valentine
NLP & LLM Real World Data Scientist
I sent my team through this training for upskilling, and the results have been remarkable. Within weeks, they became much more efficient at building automations and deploying AI agents at work. This program bridges the gap between theory and practice and it’s had a real impact on our productivity.
Aamir Faaiz
CEO of Bayseian