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Mentorship · Project-Based

Build industry-grade projects, and a moat AI can't fill for you. Not one more LeetCode problem.

Includes algorithms, OOD, system design, behavioral questions, custom industry projects, mock interviews, resume rebuilds, and referrals. The focus is on shipping production-grade distributed systems reviewed to a staff-engineer standard — building the foundational thinking that makes you a stronger engineer. Create resume projects most candidates can’t fake. Whether you’re a student or a few years into your career, this program delivers.

Start applicationSee the tracks
  • Algorithms, OOD, system design, behavioral questions, mock interviews, resume rebuilds, and referrals — all included.
  • Built around shipping high-standard production distributed systems: two capstones plus 10 mini-projects leave no gaps on your resume.
  • Referrals from past mentees now at top companies, GSoC support, and Day-1 onboarding prep — the full path.
  • For engineers and students who want to build their core engineering moat while job-hunting.
Outcomes

$218k

Median total compensation at placement.

Graduates now at FAANG or unicorns
Since 2022 · 14 companies
61
Google Summer of Code selections
2 in 2023 · 3 in 2024 · 5 in 2025 · 3 in 2026
13
Graduate stories

Three engineers from different backgrounds, three different gaps.

01
THE ACADEMIC · Cornell MS CS · 3.9 GPA

Master's degree to Meta

“I was ghosted by every recruiter despite my 3.9 GPA. The project gave my resume the signal it was missing.”

$240k
Meta E3 · Total comp

I was finishing my Master's at Cornell with a 3.9 GPA. I had the theory down cold—I could solve Hard LeetCode problems in 20 minutes. But I wasn't getting interviews. My resume was just a list of coursework and toy projects.

I realized that in this market, a degree isn't enough. Recruiters are looking for builders. My resume looked exactly like every other new grad's: generic and theoretical.

ABX changed the trajectory. We didn't just build another To-Do app; we built a distributed online moderation system to solve a real problem at scale. It wasn't a tutorial—it was engineering.

Suddenly, I wasn't getting ghosted. In my Meta interview, when they deep-dived into my resume, I didn't freeze. I explained why we chose specific trade-offs for real-time moderation. That depth got me the offer.

02
THE CLIMBER · Startup Senior → Google L5

Breaking senior-title inflation

“I had the 'Senior' title for years, but Big Tech kept down-leveling me. I needed to prove I had L5 depth.”

L5
Google · Senior SWE

I'd been a 'Senior Engineer' at a mid-sized startup for four years. I was shipping features and mentoring juniors, so I thought I was ready for FAANG. I was wrong. Every interview resulted in an L4 offer.

The feedback was brutal but fair: I was great at execution, but weak on high-level architecture. I was stuck in the weeds of implementation.

I joined ABX to force myself to think bigger. The curriculum pushed me to design systems that handle millions of QPS, not just thousands. We dissected real-world architectures like Kafka and Cassandra.

In my Google onsite, I drove the system design discussion. I anticipated bottlenecks before the interviewer pointed them out. I finally got the L5 offer I'd been chasing for two years.

03
THE GRINDER · UCSD CS · 3.1 GPA

Average grades, top-tier offer

“I wasn't the smartest kid in my class. I just needed a blueprint that actually worked.”

L4
Amazon · SDE I

Let's be honest—I'm not a genius. I went to UCSD, a great school, but my GPA was a 3.1. I struggled with Dynamic Programming. I saw my classmates getting offers at Google and felt completely left behind.

I didn't need more 'hacks' or 'tricks'. I needed a rigorous, structured plan. ABX provided that discipline. It wasn't a magic pill; it was a lot of work. But for the first time, I knew exactly what to work on.

I followed the roadmap religiously. A full year of deep dive into backend engineering principles. No shortcuts.

I didn't get into every company I applied to, but I got the one that mattered. I secured an SDE I offer at Amazon. For a strictly 'average' student like me, that changed my life.

Production engineering

Schools teach algorithms. AI writes the code. We teach the judgment that directs both.

Three tracks: Backend, Data, AI Infra. None of them is about a framework's syntax; you can pick that up from AI in an afternoon. They're about getting each domain's fundamentals into your bones: how data moves, how systems fall over under load, why a design has to be the way it is. Only once you truly understand that can you direct AI to build something that holds, instead of getting pulled around by whatever code it spits out.

Track 1

Backend SDE

Services, stores, and scale that a product-side backend engineer ships in production. JVM or Go, classical OLTP, async messaging, and the deployment surface around them.

See the roadmap
Core
You ship production code in these.
  • Java + Spring Boot
  • PostgreSQL
  • Redis
  • Kafka
  • gRPC
  • Docker
  • Kubernetes
  • AWS
Exposure
Deployed, debugged, or benchmarked inside capstone work.
  • Cassandra
  • DynamoDB
  • MongoDB
  • Elasticsearch
  • RabbitMQ
  • Prometheus
  • Grafana
  • Jaeger
  • OpenTelemetry
  • Terraform
  • Nginx
  • Consul
Track 2

Data Platform

Batch, stream, and lakehouse infrastructure that a data-platform engineer owns end to end. Kafka is the shared backbone; everything else answers to scale, latency, and correctness.

See the roadmap
Core
You ship production code in these.
  • Apache Spark
  • Apache Flink
  • Kafka
  • Airflow
  • dbt
  • Iceberg
  • Snowflake
Exposure
Queried, tuned, or integrated against on capstone work.
  • Databricks
  • ClickHouse
  • Druid
  • Trino
  • Airbyte
Track 3

AI Infrastructure

The engineering discipline around LLMs in production — serving, retrieval, agents, evaluation. Backend fundamentals applied to the 2026 hiring boom. This track trains AI infrastructure engineers, not model researchers — no training loops, no gradient math.

See the roadmap
Core
You ship production code in these.
  • Python
  • Ray
  • vLLM
  • LangChain
  • PyTorch
  • Qdrant
  • Kubernetes
  • NVIDIA
Exposure
Integrated, benchmarked, or orchestrated against on capstone work.
  • Hugging Face
  • OpenAI
  • Anthropic
  • Temporal
  • MLflow
  • ONNX
  • Ollama
  • Milvus
The work

Learn by doing.

The center of gravity is shipping projects. You don’t just study for interviews — you build the systems first, develop deep thinking of your own, and interviews become effortless.

  1. 01

    Two capstones + 10 mini-projects

    We start by building 10 targeted mini-projects to lock in your fundamentals — from database internals and distributed consensus to vector search, RAG, and agent evaluation (depending on your track). Once the foundations are solid, we move to two capstone projects — real, production-grade distributed systems.

  2. 02

    Reviewed at the staff-engineer bar

    Every project goes through real 1-on-1 code review with a senior mentor — architecture, trade-offs, failure handling, tests. You ship to the standard a staff engineer would sign off on, not 'it runs on my machine.'

  3. 03

    The complete curriculum behind it

    Algorithms, advanced algorithms, OOD, and system design — the same full course system as the flagship, so your fundamentals keep pace with what you're building.

  4. 04

    Mock interview loops + OA

    Coding, behavioral, debugging, and AI-round mocks, plus OA drills and a 100+ question behavioral bank. Rehearse the real loop until it's routine.

  5. 05

    Resume, LinkedIn & GitHub brand

    Your resume gets rebuilt around systems you genuinely own — easily passing ATS screening — and your LinkedIn and GitHub are polished too (project repos, open-source contributions).

  6. 06

    Referrals, GSoC & Day-1 prep

    Every past mentee now at a top tech company becomes part of your network for referrals, plus GSoC application support and Day-1 onboarding prep.

  7. 07

    Comp negotiation

    Strategies that have turned $160k offers into $200k+ packages. Honest levers, not theater.

  8. 08

    A moat that compounds

    The work is yours to keep and keep building. It pays off in this search, the next promotion, and the search after that — career capital, not a one-time cram.

Always ready

An AI co-pilot system built for SWE learning.

Mentors guide you. Projects prove your skills. And an AI study companion monitors your learning quality so you stay on track.

Tracks where you're weak
Across 400+ system-design problems and the two capstones, it sees which concepts you keep getting wrong — and schedules the next session around them.
Simulates the loop
On-demand behavioral, coding, and system-design mock interviews, with feedback calibrated to Google, Meta, and top-startup standards. Walk into real interviews with confidence.
Private to you and your mentor
Every practice session, every attempt, every review note is visible to your mentor before the next class. Knowledge transfer, done efficiently.
The receipts

No claims. Just screenshots.

Real offers, WeChat threads, and messages from students who made it. Names and avatars are blurred for privacy.

MENTOR

FAANG Veteran

10+ years specializing in distributed systems.
L3 → L7 → CTO.
I've walked the path you want to take.

Serial Entrepreneur

3-time founder. All ventures backed by top-tier VCs.
This isn't just coding; it's about building value.

Hiring Expert

1000+ technical interviews. ~100 interviewers trained.
I know exactly why you're failing interviews, and
how to fix it.

Common Questions

Everything you need to know about the program, the projects, and what you'll walk away with.

Fall cohort · Applications close September 30

Apply to the Project-Based program.

The application is short — about a minute if your situation is simple. If it’s complex, feel free to share everything with us. We’ll tell you honestly whether the program is a fit.

Start application

All three of ABX’s programs share one application — just tell us which one you want on the way in.

Format
1 year · 1-on-1 · remote
Commitment
~10–20 hrs / week
Tracks
Backend · Data · AI Infra
Includes
Curriculum · projects · resume · mocks · referrals
Project-Based Mentorship | ABX