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Become an AI Evaluation Engineer in 5 weeks

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Become an AI Evaluation Engineer in 5 weeks

Live (Zoom) • Intermediate • 💎 10000

Part of AI Career Accelerator

Become an AI Evaluation Engineer in 5 weeks

The only hands-on, project-based bootcamp that teaches you to test, measure, and improve AI systems — the skill every AI team is desperate to find.

Book Your AI Career Consultation
Become an AI Evaluation Engineer in 5 weeks

Duration

5 Weeks

Prerequisites

1+ yrs experience in QA

Background

Good for Noncoders

Format

Live, Hands-On Training

Upcoming Cohorts

Cohort October 2026

Start Date: October 17, 2026

End Date: November 15, 2026

Duration: 5 Weeks

Format: Live online sessions with interactive components

Instructors:Amanda Curtis, Igor Dorovskikh, Tagir Fakhriev, Alex Kiperberg

Pricing

$2,497

$2,997

Save $500

Ends soon

or Buy Now, Pay Later with Klarna Badge (only for United States)

Secure your spotLimited seats available

Course Schedule (PDT)

October 17

Saturday

10:00 AM - 2:00 PM

October 18

Sunday

10:00 AM - 2:00 PM

October 24

Saturday

10:00 AM - 2:00 PM

October 25

Sunday

10:00 AM - 2:00 PM

October 31

Saturday

10:00 AM - 2:00 PM

November 1

Sunday

9:00 AM - 1:00 PM

November 7

Saturday

9:00 AM - 1:00 PM

November 8

Sunday

9:00 AM - 1:00 PM

November 14

Saturday

9:00 AM - 1:00 PM

November 15

Sunday

9:00 AM - 1:00 PM

Everything is hands-on. You build real evaluation suites from week one.

LLM Behavior Testing

LLM Behavior Testing

Prompt injection, jailbreaks, hallucination detection, context window limits

Evaluation Frameworks

Evaluation Frameworks

Build automated evals with Promptfoo, custom metrics, and assertion suites

Bias & Fairness Auditing

Bias & Fairness Auditing

Identify and document model bias across demographics and edge cases

Safety & Red-teaming

Safety & Red-teaming

Adversarial testing, compliance checks, and responsible AI validation

Differentiators
Bootcamp cohort imageBootcamp cohort imageBootcamp cohort imageBootcamp cohort image
“Every course teaches something different — none connect together.”
“I don’t want hype or theory. I need real skills I can use at work.”
“I know AI matters, but I don’t know where to start.”
“I’m afraid of choosing the wrong course and wasting time.”
“I can’t quit my job to ‘learn AI full time.’”
“I don’t know which AI role actually fits me.”

Is this program for you?

  • QA Engineers and SDETs who want to stay relevant as AI reshapes software testing
  • Automation Engineers looking to expand beyond traditional frameworks into AI system testing
  • Manual Testers without any programming background, ready to learn from scratch, hands-on.
  • Test Leads and QA Managers responsible for quality, risk, and governance in AI-powered products
  • Software Engineers exploring AI-adjacent roles such as prompt engineering or AI quality

“I know how to test APIs and UIs… but AI apps feel different.”

→ This path bridges that gap.

quotes

Be Fully AI Job-Ready by Graduation

Career readiness isn't an afterthought — it's part of the program. You'll get dedicated coaching, a strategy to grow your LinkedIn presence, and real project experience you can speak to in any interview.

LinkedInLinkedIn
portfolioPortfolio

Get mentorship, job opportunities and peer support throughout Discord community, plus a network that stays with you.

portfolioJob leads
peopleCommunity

AI isn't replacing you. It's your next career move.

Why learning AI & LLM Testing is a must for Every QA in 2026?

AI Evaluation Engineering is already a specific, high-demand skill

AI Evaluation Engineering is already a specific, high-demand skill

More than 3,000+ job openings across the US

More than 3,000+ job openings across the US

Top AI Evaluation Engineers earn over $300K/year

Top AI Evaluation Engineers earn over $300K/year

AI Testing Skills are in-demand in every company

AI Testing Skills are in-demand in every company

Differentiators

You After the "Break Into AI Testing: AI & LLM Testing Bootcamp" Course

avatar image

AI Evaluation Engineer

Portfolio-ready AI and LLM testing experience built on a real U.S. startup project with live, hands-on training.

$200,000

Expected salary

Skills

LLM evaluation
Hallucination + factual drift detection
Multi-model comparison
LLM-graded assertions
Prompt injection + jailbreak testing (red teaming)
Bug reports for AI failures

Tools

PromptfooPromptfoo
LM StudioLM Studio
AgentaAgenta
Arato.aiArato.ai
OpenAI APIOpenAI API
Anthropic APIAnthropic API

Proof of Work

EU logo image

Break Into AI Testing: AI & LLM Testing Bootcamp

EnGenious University

AI Application Testing Portfolio

Hands-on artifacts covering LLM evaluation, prompt injection and jailbreak testing, multi-model comparison, and hallucination detection — built using Promptfoo, OpenAI API, Anthropic API, and LM Studio.

Will I get a certificate?

Of course! It'll look great on your resume and LinkedIn

Certificate Background
EnGenious University Logo

Your Name

Break Into AI Testing: AI & LLM Testing Bootcamp

Instructors:

Amanda Curtis, Igor Dorovskikh, Tagir Fakhriev, Alex Kiperberg

Finished: November 15, 2026

Number of lectures: 10 / Total hours: 40

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university.engenious.io
university@engenious.io

Our alumni work at

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Hershal Walton linkedin icon

Gen AI Product Manager

“This course puts you in a leading frontier for new opportunities that should be coming up very soon”

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Max Volovich linkedin icon

QA Engineering Manager @ Sirona Medical

“After this course, I not only understand how AI systems work behind the scenes, but I also feel confident leading teams building and testing them.”

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Mavis Herring linkedin icon

AI Quality Engineer @ WeOptimize AI

“This course built confidence. As soon as I posted that I finished the course on LinkedIn, many recruiters started approaching me.”

Our alumni work at

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We've taught 1,000+ students to ...

Learn From The Best

Igor Dorovskikh
Igor Dorovskikhlinkedin

CEO and Founderengenious icon

Igor is an accomplished CEO and Founder of Engenious.io, with 15+ years of experience in software testing and development and over a decade in management. He has worked at Barnes & Noble, Expedia, Tinder, and consulted at Apple and Grammarly. In the mentorship program, Igor offers expertise in building a testing process from scratch, leadership success, understanding C-level executives' expectations, selecting the right technology stack, providing and collecting feedback, and team growth. Mentees benefit from Igor's insights on creating efficient testing processes, fostering productive teams, aligning with executive priorities, making informed technology choices, establishing feedback channels, and securing resources for team development. With Igor as their mentor, participants gain valuable knowledge, skills, and perspectives to excel as Dev/QA Directors or Managers.

Read more
Jaime Mantilla
Jaime Mantillalinkedin

Quality Engineering Managerengenious icon

Seasoned IT professional with 14+ years of experience in Software Engineering, Quality Assurance, and Automation. Skilled in leading teams, designing test strategies, and building automation frameworks across diverse industries. Adept at leveraging modern tools, AI-driven testing approaches, and cloud technologies to deliver high-quality, scalable solutions. Holds a Bachelor’s in Management Information Systems and a Master’s in Information Technology with proven success supporting enterprise-level clients and Fortune 500 companies.

Read more
Amanda Curtis
Amanda Curtislinkedin

Founder of Lemonade Tech & QA Managerengenious icon

Amanda Curtis is a QA leader and founder of Lemonade Tech, with a passion for responsible AI adoption and helping teams cut through tech overwhelm. With 10+ years experience leading QA teams and modernizing testing practices, Amanda focuses on practical solutions that improve software quality while keeping technology approachable and human-centered. Helping organizations “find the good in tech” by cutting through complexity and focusing on what truly adds value.

Read more
Tagir Fakhriev
Tagir Fakhrievlinkedin

Software Engineerengenious icon

10 years of experience in the tech industry; Senior Android Engineer in Platform team. Expert in CI/CD pipelines, test automation, and mobile infrastructure; passionate about developer productivity and workflow optimization.

Read more
Gregory  Goldshteyn
Gregory Goldshteynlinkedin

Instructor AI Acceleratorengenious icon

Visionary QA Leader with substantial experience in the IT industry. Worked across Salesforce, Sony, and now as part of Video Engineering and Quality Assurance, he leads the strategy for high-concurrency streaming environments, where a single second of latency is unacceptable.

Read more
Alex  Kiperberg
Alex Kiperberglinkedin

Instructor AI Acceleratorengenious icon

Software development and QA experience for over 20 years. Alex has worked at well-known companies such as Oracle and HCL Software, and has strong expertise in functional, regression, and automated testing, complemented by a background in Java-based application development. Skilled in WebdriverIO, Selenium, JavaScript, and CI/CD pipelines, with hands-on experience in building and supporting enterprise applications.

Read more
Vladimir Tanev
Vladimir Tanevlinkedin

Senior iOS Engineer to Co-Founder & CTO·WeOptimize.ai engenious icon

Vladimir is an experienced engineer with 8+ years in iOS/macOS development, specializing in AI-powered solutions.  As the Co-Founder & CTO of WeOptimize.ai, he leverages AI to optimize workflows and enhance productivity. He has a track record of delivering innovative products for both startups and large enterprises.

Read more
Max  Volovich
Max Volovichlinkedin

Instructor AI Acceleratorengenious icon

Quality Engineering leader driving scalable automation and delivery across enterprise SaaS and AI/LLM systems. Leads global QA teams and embeds quality into revenue-critical release pipelines, strengthening reliability and trust in AI-driven products.

Read more

What you'll achieve in 5-weeks

01

Week

Day 1: AI Fundamentals and Tool Setup

Introduction: Course rules, setting up the permanent Discord community channel. Theory: LLM basics, transformer architecture, differences between traditional software testing and AI system testing.

Hands-on: Environment setup (local and cloud models). Initial interactive model exploration comparing local (LM Studio) and commercial (OpenAI, Anthropic) models using the same prompt. Vulnerabilities: Introduction to the seven unique AI testing challenges (e.g., security, hallucination, bias).

Homework: Complete environment setup and design 3+ test prompts targeting the vulnerabilities.

Day 2: PromptFoo Basics

Tool Introduction: Learning PromptFoo for systematic AI testing. Shift to hands-on, Q&A, and group exercises (minimal presentations).

Configuration: Overview of PromptFoo's configuration (YAML structure), including providers (LLMs), prompts, and initial deterministic assertions (pass/fail checks). Practice utilizing variables within prompts.

Integration: Testing commercial and local models via PromptFoo.

Homework: Practice building test suites and reviewing assertions documentation.

02

Week

Day 4: Advanced Assertion & Career Prep

Advanced Testing: Deep dive into assertions, particularly Model-Graded Assertions (MGA), where an LLM acts as a judge (LLM Rubric) to evaluate output quality (relevancy, factuality). Testing using CSV-based files for structured test data.

Career Start: Introduction to LinkedIn Personal Branding; documenting early achievements and incorporating AI testing keywords (e.g., prompt engineering, LLM testing) to profiles.

Homework: Review PromptFoo Red Teaming documentation.

Day 3: Prompt Engineering and Cost Evaluation

Prompt Engineering: Defining the rules and constraints of the system (System Prompt) and crafting effective test inputs (User Prompt). Using AI (LLMs) to generate effective test prompts.

Evaluation: Hands-on workshop on LLM cost evaluation (budgeting) by running prompts against multiple models to compare cost per request.

Organization: Structuring the testing framework using file-based prompt configurations.

03

Week

Day 6: Testing a Real Application (Red Team Web App)

Application Architecture: Reviewing the high-level architecture of the application (Orchestrator, Guard LLM, specialized LLMs, knowledge bases like Jira/Confluence/Figma).

Testing Mode: Focusing on end-to-end black box exploratory testing via the application's chat interface. Using the provided "Source of Truth" as acceptance criteria.

Bug Reporting: Hands-on exercise reporting and documenting bugs, including reproduction steps and linking them to specific AI vulnerabilities.

Day 5: Red Teaming Concepts

Equator Point: Course halfway review.

Red Teaming: Defining red teaming as simulating adversarial inputs (like a comprehensive baseline report) to find vulnerabilities (e.g., security, bias). Discussion of vulnerability frameworks like the OWASP Top 10 for AI.

Strategy: Understanding Red Teaming workflow (defining strategy, execution, analysis) and configurations. Comparison of red teaming types (Small, Large, XXL/Extensive).

04

Week

Day 8: Tool Exploration & Post-Launch Monitoring

Post-Launch Tools: Demo and discussion of tools used for monitoring and maintaining LLM models pre- and post-launch (e.g., Arato wrapper).

New Tool Assignment: Introduction to Agenta (a comparable, alternative LLM testing platform).

Homework: Explore and evaluate Agenta to apply foundational testing concepts learned from PromptFoo. Research other AI testing tools in the market (consulting mindset).

Day 7: Red Teaming Execution & Triage

Application Setup: Finalizing the Red Teaming configuration by inputting a comprehensive application context (main purpose, features, system rules) into PromptFoo.

Group Triage: Teams exchange reported bugs and attempt to reproduce and validate issues found by classmates.

Advanced Testing: Hands-on session applying PromptFoo for complex scenarios, including multi-turn conversation testing using JSON objects for regression.

Tool Exposure: Alternative testing tool.

05

Week

Day 10: Final Optimization & Interview Prep

Final Profile Optimization: Updating LinkedIn profiles and resumes with core AI testing skills (prompt engineering, red teaming, hallucination detection, token consumption).

Interview Preparation: Review of common AI testing interview questions (e.g., scaling tests, verifying factual responses, token consumption, security, testing LLMs with other LLMs).

Wrap-up: Final remarks, community engagement commitment, and discussion of post-course resources.

Day 9: Agenta Review & LinkedIn Strategy

Tool Comparison: Reviewing homework findings on Agenta, applying foundational concepts (Evals, variables) learned from PromptFoo to a new platform.

Career Branding: Strategies for content creation and influence building on LinkedIn. Using generative AI tools (e.g., Claude, ChatGPT) as brainstorming partners for posts, while avoiding generic copy-paste content.

Accomplishments: Workshop focused on drafting AI LLM testing accomplishment statements for resumes/profiles, quantifying the business impact of skills learned.

Homework: Post tailored AI testing content on LinkedIn and engage (comment/repost) with classmates' posts.

Benefits You Won't Find Anywhere Else

Lifetime Community Access

Join our Discord community with 1000+ QA professionals.

Join our Discord community with 1000+ QA professionals.

Ongoing support from instructors and alumni.

Ongoing support from instructors and alumni.

Regular follow-up sessions and career guidance.

Regular follow-up sessions and career guidance.

Differentiators

Recorded Sessions

All sessions recorded and can be accessed up to for 1 year.

All sessions recorded and can be accessed up to for 1 year.

Review program materials and session recording anytime.

Review program materials and session recording anytime.

Never miss important concepts.

Never miss important concepts.

Differentiators

What's Next? Even More

Of course, after completing the course, you can start working. But you should not stop your development. We are the only ones who offer not one course, but a comprehensive path that will make you a professional.

Two weeks after completing the course, the best students will be able to do an internship with us. During the internship, you will be directly involved in ongoing projects related to Stella Foster, our communication platform based on artificial intelligence.

You can also upgrade your knowledge with the Advanced RAG & Multi-Agent Testing course, which will make you the most sought-after employee in your field.

02
Special offerOnly for the best students

Internship in AI Startup (Stella Foster)

  • Live
  • Intermediate
  • 4 weeks

Take your skills further with a hands-on internship designed to give real-world experience working with production AI systems, testing frameworks, and voice/SMS automation tools.

03

Advanced RAG & Multi-Agent Testing

  • Live
  • Advanced
  • 8 Weeks (32 hours)

Go deep into Retrieval-Augmented Generation, vector databases, grounding, multi-agent workflows, tool usage, and complex evaluation frameworks used in modern AI systems.

System Requirements

Minimum system requirements

macOS:

macOS:

Processor: Apple Silicon M1, M2, M3 or M4

Memory: 16 GB RAM (or higher)

Storage: 30 GB free SSD space

Note: Mac OS systems without an M chip are not supported

Windows:

Windows:

Processor: Intel Core i5 / i7 or AMD Ryzen 5 / 7

Memory: 16 GB RAM (or higher)

GPU: Dedicated GPU with ≥ 6 GB VRAM (e.g., NVIDIA RTX 2060 / 3060)

Storage: 30 GB free SSD space

FAQ

Submit your application and confirm your eligibility — only 50 seats per cohort are available. Early applicants receive priority for personalized feedback and project pairing.

Not sure if the program is right for you? Book a free AI Career Strategy call before you enroll.

Yes — at least 1 year of QA experience (manual or automation).

No programming background is needed, though familiarity with testing workflows is helpful.

1. Project-based learning: You test a real U.S. AI startup product

2. 95% hands-on: Minimal theory, maximum practice

3. Mentor-led live sessions (with recordings for 1-year access)

4. Career coaching and interview prep built into the final module.

Week 1: AI fundamentals, environment setup, and AI-assisted testing basics

Week 2: LLM testing, debugging model failures, and assertion strategies

Week 3: Advanced red-teaming, grounding validation, and safety testing

Week 4: Open-source tools, workflow automation, and model evaluation frameworks

Week 5: Resume optimization, job prep, and final capstone showcase

You’ll gain practical skills to:

1. Test and validate AI-powered applications and LLMs

2. Detect hallucinations, bias, and factual drift

3. Evaluate grounding and context reliability

4. Use frameworks like Promptfoo and LLM-graded assertions

5. Build a portfolio-ready capstone project aligned with current job roles

These are addressed through:

- Deterministic & weighted assertions

- LLM-graded accuracy evaluation

- Safety, bias, and hallucination detection patterns

- Multi-model comparison

- Context-based grounding checks

Weeks 2–3 focus on advanced Promptfoo assertions and red-team strategies to identify hallucinations, factual drift, and grounding violations.

You won’t build a RAG pipeline from scratch, but you’ll learn how to evaluate retrieval-augmented systems — a core QA responsibility in AI production environments.

This program is for QA professionals with 1+ year of manual QA experience who want to move into the fast-growing world of AI Quality Assurance.  No coding or AI experience is required — just curiosity, analytical thinking, and a testing mindset.

Yes — these are included through:

1. Drift indicators and re-evaluation cycles

2. Synthetic variation testing

3. Failure pattern analysis

3. Feedback loop triage

You’ll learn to identify regression behaviors and emergent defects as AI systems evolve — essential for real-world QA teams.

Yes, but in this course. "Break Into AI Testing" bootcamp focuses exclusively on text-based LLMs, since the current job market is centered on grounding, factuality, and safety validation for text systems.

To all of the alumni as a part of our AI Career Accelerator path we offer a next Advanced course focused on the more kinds of AI.

AI Career Accelerator is a long term path aimed at full career transformation that offers various courses about AI testing and internship opportunities.

"Break Into AI Testing" - is a first step of AI Career Accelerator path, a 5-week, hands-on training program designed to help QA engineers transition into AI & LLM Testing roles. You’ll work on a real U.S. startup AI project while mastering model evaluation, red-teaming, and test automation with AI tools.
 

You’ll explore multi-agent orchestration concepts by testing a live AI app (WeOptimize).

We emphasize end-to-end testing rather than isolated stages.

You’ll learn to:

✅ Identify failure points in multi-turn interactions

✅ Evaluate guardrail effectiveness and memory behavior

✅ Detect safety leaks and context loss across chained logic

✅ This reflects real QA work in AI product teams — black-box testing of complex reasoning flows.

💻 Windows

✅ Windows 10 (64-bit) or newer

✅ Intel i5 (8th Gen +) / AMD Ryzen 5 +

✅ 8 GB RAM (min), 16 GB recommended

✅ 20 GB free storage

✅ Node.js v18+, Python 3.8+, VS Code, Git (Docker optional)

✅ Chrome or Edge browser

✅ Stable 10 Mbps+ internet + webcam


🍏 macOS: macOS Monterey (12+) or newer

✅ Apple M1/M2 chip or Intel i5 (2018 +)

✅ 8 GB RAM (min), 16 GB recommended

✅ 20 GB free storage

✅ Homebrew, Node.js v18+, Python 3.8+, Docker (optional)

✅ Chrome or Safari browser

✅ Reliable 10 Mbps+ connection + webcam

💡 Tip: Dual-monitor setups improve productivity for labs and evaluations.

The training is a 5-week long training. It includes 10 lectures (40 hours). Classes are held on weekends, Saturdays and Sundays from 10.00 am to 2.00 pm PST

Yes — we provide comprehensive career preparation and mentorship support, though employment is not guaranteed.

During the final week of the cohort, we dedicate 4 hours to focused career development sessions covering:

  • LinkedIn optimization and personal branding
  • Job search strategies tailored to AI and QA markets
  • Resume updates and portfolio positioning for AI Testing roles

For top-performing graduates, Engenious may offer short-term contract roles through partner projects or internal initiatives. However, timelines and availability are not guaranteed.

After graduation, you can continue growing through our Mentorship Program — designed to help you refine your AI QA skills, gain real-world experience, and stay connected with the Engenious professional network.

Yes, currently available for U.S. and Canada applicants. May be available for other countries - only for U.S. Dollars payments.

During checkout, you can select a payment plan through Stripe’s Klarna interface, allowing you to spread tuition into manageable installments.

Still have questions?

Not sure if this program is right for you? Need help choosing the best path or want to understand the curriculum better

Our AI assistant is here to help — fast, friendly, and available anytime.

Ask AI CAREER ASSISTANTcool robot hand image

100% money back guarantee

If you're not satisfied by Week 1, claim a full refund, no questions.

Seats are limited to 50 registrants. Secure your spot today.

Ready to begin your AI testing journey?

The future of QA isn't about choosing between Selenium or Playwright - it's about Mastering Prompt Engineering, LLM Testing and AI Debugging.

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