Build Your AI Portfolio: Land AI Engineer, FDE and AI PM Roles
Dr. Aki Wijesundara
PhD in ML | Google AI Accelerator Alum
Manu Jayawardana
Exited AI Founder | Founder, TAI Labs
Ship one production-grade AI project with evals and a story in 3 weeks.
You’ve done the courses. You’ve built the RAG chatbot. But when a hiring manager opens your GitHub, nothing proves you can take a messy real problem to something reliable, measured and explainable. That is what AI Engineer, Forward Deployed Engineer and AI PM interviews screen for, and demos don’t show it.
In 3 weeks you’ll fix that. You’ll pick a realistic business problem, build an agentic system around it with Claude Code, prove it works with a proper eval report, and package it into a portfolio piece written for the role you want.
Week 1: scope a real problem and ship a working v1
Week 2: build a golden set, a failure taxonomy and before/after numbers
Week 3: public repo, demo video, case study, demo day with a hiring panel
One core build, three role tracks. AI Engineers leave with an eval harness and architecture record. FDEs leave with a discovery doc and deployment plan. AI PMs leave with a PRD and metrics plan.
TAI courses are built and taught by practitioners who ship agentic systems for real clients every week. 10,000+ professionals trained. Alumni from OpenAI, Google, Meta, McKinsey and BCG.
The app is the evidence. The proof is the product.
What you’ll learn
Practice the three skills that make senior people listen: a sharp narrative, command of the room, and composure under pressure.
Pick from 10 realistic business problems with datasets, or bring a real client workflow
Write a one-page brief with a named user, the workflow today and a success metric
Scope it so an interviewer can grasp it in 5 minutes
Retrieval, tool use, an agent harness, guardrails and structured outputs
Decide when you need a single prompt, a pipeline or an agent
Ship a working v1 by the end of Week 1
Build a golden set of 30+ cases including edge cases and adversarial inputs
Categorise every failure and fix the top three, with before/after pass rates
Measure cost and latency per request like a production team
Public repo with a README a hiring manager can read in 3 minutes
3-minute demo video and a one-page case study written for your target role
Map every artefact to the interview questions it lets you answer
AI Engineer: architecture decision record and eval harness
FDE: customer discovery doc and deployment plan
AI PM: PRD, metrics plan and launch criteria
5-minute presentation followed by interview-style questions from working hiring managers
Best projects get featured across TAI channels
Learn directly from Aki & Manu
Dr. Aki Wijesundara
AI Founder | Educator | Google AI Accelerator Alum
Manu Jayawardana
AI Advisor | Founder, TAI Labs
Who this course is for
The Engineer moving into AI. Has done a bootcamp or two. Needs proof of production judgment, not another demo.
The aspiring Forward Deployed Engineer. Can build, but has no customer-facing deployment story to tell in interviews
The PM targeting AI roles. Expected to spec and evaluate AI features. Needs a shipped example with real metrics
Prerequisites
One AI course or bootcamp completed
You should have built at least one LLMpowered project before. This course is about proof, not first steps
Comfortable with Python or TypeScript, or driving Claude Code
Engineers write code. PMs spec and drive a Claude Code build. Either path works, but you must be able to run a project locally.
Around 6 hours a week
Two 90-minute live sessions plus 3 hours of building. Every Friday has a shipping deadline.
What's included
6 live sessions
Two 90-minute hands-on sessions a week across 3 weeks, each with a role-track breakout for AI Engineers, FDEs and AI PMs
10 ready-made project problems with datasets
Realistic business problems with personas, synthetic datasets with deliberate noise, hand-labelled golden sets and target metrics. Pick one and start building on day one.
Live partner projects
A limited number of seats to work on a real workflow from a partner business, with feedback from the actual user. First come, first served
Reference build and templates
A complete worked example taken through every stage, plus templates for the brief, README, eval report, case study, PRD, discovery doc and architecture record.
Starter repo with eval harness
Clone and go. Config, logging, a run entry point and an evals folder with a scoring script and report template.
Demo day with a hiring panel
Present your project to Aki and guest hiring managers and field interview-style questions. The rehearsal you never get before the real thing.
Weekly office hours
Build help every Wednesday. Bring your bugs.
Lifetime access
All recordings, repos, datasets and templates, plus complimentary access to a future cohort
Certificate of completion
Issued when you ship the full portfolio piece and present on demo day
Maven Guarantee
Your purchase is backed by the Maven Guarantee.
Course syllabus
Week 1
Image Generation
Video Generation
Workflow & polish
Key takeaways + next steps
Resources
Articles
Useful Interviews
Jul
28
Executive Presence: Live Class
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.
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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
Hear It From Our Students
Learning AI Made Simple | Student Feedback on Our AI Engineering Bootcamp | TAI
Who You'll Be Learning From
Learn from Aki & Manu. Previous students are from top companies like Google, Meta & OpenAI.
Here’s what our cohort members are saying
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Frequently asked questions
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