Get 1:1 mentorship, coaching, and guidance from Tier-1 architects
AI Systems Engineering
Academic partners
Want a top-tier role? Here's how you get there:
Build real-world projects. Ship production-grade systems.
Practice technical and HR interviews so you can excel at the real thing
Henrietta, coach
Ji-ho
Is this career accelerator for you?
“You should have two years of software development experience, or similar experience in QA, DevOps, or another role with production systems.”
“You should have two years of software development experience, or similar experience in QA, DevOps, or another role with production systems.”
Dr. Gönen ErenCurriculum AuthorWho you areYour skill gapsHow you'll bridge them
Who you are
Backend & Fullstack Engineers
You create APIs and business logic, but need skills in distributed systems and AI.
Your skill gaps
System decompositionMonolith scalingData consistency
How you'll bridge them
- Build full-scale production system across 5 progressive projects
- Defend your architecture 1-on-1 with Senior Engineers
Who you are
Infrastructure, DevOps & SRE
You manage pipelines and uptime; complex AI workloads need new performance approaches
Your skill gaps
Cloud & K8s for AIAdvanced observabilitySecurity review
How you'll bridge them
- Target only your gaps with modular theory
- Get weekly 1-on-1 mentorship to debug your code or real work cases
Who you are
Data Engineers & Tech Pros
You have a STEM background but lack experience in distributed systems design
Your skill gaps
Architecture & API designCloud/DevOpsSystem Design interviews
How you'll bridge them
- Fill technical gaps with optional theory tracks
- Practice mock technical and HR interviews with debriefs after every round
If you are switching careers into tech for the first time, explore our other programs
Career switching programsWork with a senior engineer from day one
Day 1
Meet the mentor you'll work with one-on-one for the entire program.
During the program
Mentors assess your architecture, examining how issues were resolved and identifying failures.
Capstone
Defend your design decisions to a staff-level engineer, the same way you would to a hiring manager.
Mohamed Cherif
InstructorPrincipal / Staff Software Engineer
Dr. Gönen Eren
Curriculum AuthorExpert .NET/C# Backend Developer
Ahmed Abouzeid
InstructorSenior Engineering Leader
Support at every stage
Live engineer-led defense
Projects end with a 1-on-1 to present your architecture and defend your code
Personalized lesson plan
Skip what you already know and focus only on your specific gaps with guided support
1-on-1 mentorship
Meet weekly for 30 minutes 1-on-1 with senior engineers to review code or discuss job challenges
Mock interview practice with people
Up to 3 technical interview with engineers and 3 behavioral rounds with a coach, plus a debrief after
Your complete AI-enabled career accelerator
Mock interviews & debriefs
Practice technical & HR interviews to hone your performance and fix blind spots.
Lifelong access
Come back any time to review curriculum updates and use your alumni career coaching sessions.
Support all the way through the offer
From take-home tests
to salary negotiation support
Optimized job applications
We'll help you create job search materials that get attention.
A global network built for your career leap
Join a network of leading engineers: your peers, instructors, and 7,500 TripleTen alumni across the US and Latin America.
Work with engineers from TripleTen's partner, Nebius Group.
Powered by 800+ engineers, Nebius offers full-stack AI infrastructure services for industry leaders including Nvidia, Meta, & Microsoft.
Access the hidden job market and build your referral network while you study.
300+
Daily opportunities on our job board.
Get a chance to mentor beginner tech students. Gain leadership experience.
Cara
Hey! I'm working on the e-commerce practice set, and I'm a bit stuck on filtering and aggregating…
🤔1
Demetrus
Great question! This is where SQL really shines compared to spreadsheet tools.
❤️1Build a production-ready system that showcases your expertise
Projects first. Theory when you need it.
Focus on project work. Fill knowledge gaps with 250+ optional hours of lessons.
Five skills. One workflow.
Combine observability, RAG, cloud queues, security, and AI agents in one workflow.
Real-world engineering tradeoffs.
Learn to make decisions that mirror production engineering environments.
Apply system design principles to maintain a stable public API contract across schema migrations and underlying database refactoring.
Tools used:
RESTgRPCPostgreSQLRedis
Theory behind it
API and service architectureVersioning and deprecation strategyRelational data modelingRead replicationCache invalidationContract testing
Starting state
A running PostgreSQL cluster, a partial API spec, and active production traffic on v1.
Engineering decisions
Read replica placement, caching boundaries, and versioning/deprecation strategy for breaking changes.
Evaluation criteria
Zero disruption to existing v1 clients, backed by passing contract and integration tests.
Rely on practical problem solving to build reliable deployment pipelines and maintain observable, production-grade Kubernetes infrastructure under failure conditions.
Tools used:
ReactStorybookTailwind CSSGraphQLPostgreSQL
Theory behind it
Containers and orchestrationInfrastructure as codeCI/CD pipelinesSLOs and error budgets
Starting state
A production Kubernetes cluster, live telemetry dashboards, and an active simulated incident.
Engineering decisions
Deployment strategy, automated rollback paths, and alert thresholds/paging rules.
Evaluation criteria
Mean time to recovery (MTTR), rollback stability, and whether telemetry provides clear root-cause visibility.
Design an idempotent message-processing pipeline and secure service mesh capable of surviving network chaos and state replay.
Tools used:
KafkaOAuth 2.0VaultThreat modeling
Theory behind it
Event-driven architectureExactly-once and idempotency patternsChaos engineeringZero-trust authenticationSecrets managementAutomated security scanning
Starting state
A Kafka pipeline, an incomplete threat model, and an active chaos-engineering harness.
Engineering decisions
Idempotency key strategy, zero-trust network boundaries (mTLS/least-privilege IAM), and CI/CD security gate enforcement.
Evaluation criteria
State consistency under event replay, pipeline fault tolerance during simulated infrastructure failures, and compliance with the threat model.
Master context engineering and cost optimization to build production agentic AI features backed by automated evals.
Tools used:
RAGAgentic workflowsEvalsLLM gateway
Theory behind it
LLM gateway designRouting and fallback chainsRAG architecture and chunking strategyAgent orchestrationEvaluation harnesses
Starting state
Raw platform data for RAG, a strict token budget, and an empty evaluation framework.
Engineering decisions
Model routing and fallback logic, RAG chunking strategy, and CI/CD eval gating thresholds.
Evaluation criteria
Cost per request, quantitative retrieval metrics (e.g., precision/recall), and evals that block failing builds.
Synthesize prior projects into a unified production architecture and defend your design decisions.
Tools used:
C4 modelADRsScaling reviewRisk register
Theory behind it
Architecture documentation with the C4 modelDecision recordsTradeoff analysisTechnical communication
Starting state
Your integrated end-to-end agentic AI platform and complete system design documentation.
Engineering decisions
System trade-off justifications, technical debt prioritization, and a 10× traffic scaling strategy.
Evaluation criteria
A 60-minute technical review and architecture defense with an independent Staff Engineer.
Ready to level up?Let's talk.
Book a call with an admissions advisor to review your skills audit, get your questions answered, and pick the right program.
Repeatedly recognized and highly rated
Highly rated 6 years in a row
4.7/5
Rigorous curriculum, with academic partners including:
TripleTen in the media
How Education Is Changing In The AI Era—And Why You Should Be Excited.
TripleTen grad Jeremy Rivera traded night shifts in a warehouse for a remote developer job.
Survey: How office workers are really using AI on the job
TripleTen is the overall best Software Engineering bootcamp for 2024.
6 in 10 employees see AI as a coworker.
Most office workers say 'please' and 'thank you' to AI—and experts say it might actually matter.
Why it pays to be polite to AI — by Lee Hafner (Jun 4, 2026).
Flexible payment options
Upfront payment
Pay in a single installment, or up to 4 payments. You can withdraw with a 100% refund in your first 2 weeks.
upfront payment of
$12,600 in total$12,600
Tuition financing
Apply for financing with one of our partners, and learn if you are eligible in minutes. Soft credit check req'd.
Monthly payments starting at
$17,950 in total$350
TripleTen installments
$1,000 deposit. No credit check req'd, 0% interest. 6, 12, or 24-month plans available.
monthly payments from
$20,000 in total$792
Our financial partners for tuition financing:
Upfront payment
Pay in a single installment, or up to 4 payments. You can withdraw with a 100% refund in your first 2 weeks.
upfront payment of
$12,600 in total$12,600
Can be split into 2 or 4 payments
Tuition financing
Apply for financing with one of our partners, and learn if you are eligible in minutes. Soft credit check req'd.
Our financial partners for tuition financing:
Monthly payments starting at
$17,950 in total$350
TripleTen installments
$1,000 deposit. No credit check req'd, 0% interest. 6, 12, or 24-month plans available.
monthly payments from
$20,000 in total$792
Frequently asked questions
What is the AI Systems Engineering program?
AI Systems Engineering is a 22-week career acceleration program that takes you from feature-level work to system-level engineering. You learn to design, build, and scale production-grade systems, from distributed architectures to AI pipelines, and you graduate with a portfolio of four deployed, open-source products.
Who is the AI Systems Engineering program for?
It is built for working engineers and tech-adjacent professionals who want to level up, not start over. If you already ship features and want to architect reliable, scalable systems, including production AI, this program meets you at that next step.
Do I need to quit my job to take the program?
No. The program is designed to fit around full-time work. It runs about 22 weeks, so you can keep your current role while you build system-design skills and a portfolio that proves them.
How long is the TripleTen program and how is it structured?
It runs about 22 weeks: eight core modules, a one-week Operator UI Workshop, a five-week partner-company externship, and a capstone of four portfolio projects, ending in a final panel review. An AI In Practice thread runs through every module.
What will I learn in the AI Systems Engineering curriculum?
You cover system design, API and service architecture (REST, GraphQL, gRPC), data architecture, cloud infrastructure (Kubernetes, Terraform, GitOps, CI/CD), distributed systems and Kafka, security and compliance, AI systems design (LLM integration, RAG, model serving), and architecture documentation and technical leadership.
You'll work on context engineering, deciding what information a model sees and how it is retrieved and structured, and on agentic AI systems engineering, where autonomous agents plan multi-step work and need evaluation gates to keep their output trustworthy.
What projects will I build in the program?
You build four standalone, open-source products: OpenMon, a self-hosted Datadog alternative; StreamFlow, a visual event-pipeline engine; CloudForge, an internal developer platform; and NeuralGate, an LLM gateway and evaluation layer.
Does the program include real work experience?
You graduate with a portfolio that shows hiring managers what you can build. Engineers who work at companies like Meta, Amazon, and Google DeepMind review your projects as you go. Choose the format that suits your needs best: externships, hackathons, and technical competitions are available for AI Systems Engineering students.
What kind of support and guidance can I expect during my studies?
You'll learn from experienced engineers who work at top tech companies and receive personalized support through one-on-one mentoring sessions, office hours, code and project reviews, and career coaching. You'll also have access to live lectures and webinars covering the latest trends and in-demand topics in tech. Our curriculum is regularly reviewed and updated to align with the skills employers are looking for today.
What portfolio will I be able to show employers after I finish?
You finish with a portfolio of deployed, open-source systems you own, a real externship deliverable if you choose to take part in it, and a written panel assessment from industry reviewers. Together they are verified evidence that you can architect and ship production systems.