AMA Interview is an AI-powered platform that helps job seekers prepare for interviews through realistic mock sessions, personalized feedback, and a curated library of real industry questions.
I joined AMA Interview at the earliest stage, helping shape the product from concept to launch. As the user base grew, the company reached stable activation, steady acquisition, and recurring paid users—now evolving based on user data and monetization goals.
I joined as a UX Designer, focusing on early-stage UX/UI design and defining the product’s core experience.
As the product evolved, my role expanded to Product Designer, working with the question bank dataset and collaborating with the growth team to analyze user feedback and inform product strategy.
During my time at AMA Interview, I focused on two major projects that directly contributed to product growth and user engagement.
Scaling Interview Question Bank with AI Automation
To attract and retain users, AMA Interview needed a high-quality, continuously updated question bank. This content was essential for SEO, driving traffic, and providing value to users.
My role was to design a scalable, automated system that increased content volume without compromising quality.
At the early stage, the process of adding and updating interview questions was entirely manual—slow, resource-heavy, and error-prone. With limited time and resources, we needed to:
Automate content addition and updates.
Ensure high content quality.
Build a process that was sustainable and easy to maintain.
I collaborated with UX/UI designers and engineers to:
Design a workflow that minimized manual tasks.
Replace traditional spreadsheets with smarter work management tools.
Build an automation process that allowed non-technical team members to contribute with minimal learning curve.
Document the entire process into a repeatable, low-code solution.
We faced constant technical adjustments:
Debugged errors with engineers as platform needs evolved.
Reorganized workflows to reduce error rates.
Balanced automation with quality control through iterative testing.
Increased question bank size by 433% in a short period.
Developed a documented workflow guide, reducing onboarding time for new team members.
Laid the foundation for future AI-driven enhancements by the engineering team.
Personalized Email Marketing to Increase User Activity
With the goal of increasing user engagement, acquisition, and monetization, I led efforts to build branded email campaigns and leverage user behavior data for targeted marketing strategies. This project aimed to turn passive users into active, paying customers.
Before my involvement, there was no structured email marketing system:
No automation in place.
Lack of brand personality in user communications.
No audience segmentation for personalized outreach.
Working closely with the growth team, I:
Conducted competitive analysis to understand industry best practices.
Collaborated with engineers and SEO specialists to build email templates using HTML/CSS.
Designed and executed small-scale promotional campaigns to test messaging and tools.
Developed a user segmentation framework for more personalized targeting.
Monitored key metrics: open rate, click rate, unsubscribe rate.
Used insights to refine messaging and design for better engagement.
Continuously updated audience segmentation to align with user behavior patterns.
Reflection & Learnings
Wore many hats in a small team
In a tight-knit startup environment, roles were fluid—I often had to quickly learn new skills and apply them immediately to deliver high-quality results across design, product, and growth initiatives.
Adapted to a steep learning curve
With limited resources and fast-changing priorities, every project required rapid decision-making, creative problem-solving, and the ability to learn on the go.
Navigated shifting goals and product pivots
Goals evolved frequently as the startup searched for product-market fit. Flexibility, strategic thinking, and embracing ambiguity became essential.
The importance of strong communication
Frequent standups and open team collaboration ensured alignment across design, engineering, and growth, helping us stay focused even as direction shifted.
Iterative mindset over perfection
Working in a startup taught me that no product is ever “perfect.” Every small design improvement, experiment, or feedback loop contributes to building a better product over time.
If you’re interested in learning more about the project details, design decisions, or my process behind the work at AMA Interview, feel free to reach out. I’d be happy to share more—contact me at zhongg17@gmail.com