QA Specialist - Agent+

About the role

The role validates web application quality for multiple clients through structured testing. Collaboration with the Agent+ team and product managers guides testing priorities and issue resolution. The position helps high-growth startups improve design and development delivery speed by validating features before release.

Data roles turn raw information into decisions. Analysts query databases and build dashboards. Data scientists build models that predict outcomes. Data engineers build the pipelines that move and store data. All three work closely with business teams and need a mix of statistics, coding, and communication. Nearly every modern company runs on data teams, from startups to banks. A strong portfolio of past analyses matters more than degrees in many hiring decisions.

Key facts

What you'll do

Testing teams review features against acceptance criteria before releases to expose bugs and inconsistencies. Detailed documentation records issues and tracks progress for each client product so teams understand requirements. Collaboration with developers and product managers confirms that features undergo rigorous testing during development cycles.

Manual testing targets web applications built with React to validate functionality and design consistency. QA checks align with weekly development cycles to confirm bug fixes and new features meet requirements. Verification happens for 1-3 PRs per week that developers push and require testing before deployment.

Requirements

The posting states a bachelor's degree requirement. Understanding of web application workflows and standard testing tools supports effective validation for client products. Clear written and verbal English skills document bugs and coordinate work with global teams. A proactive mindset identifies, analyzes, and resolves issues throughout the development lifecycle.

Remote work demands self-motivation and strong organization to manage tasks independently. Familiarity with Github and related control systems enables efficient testing and version tracking.

Nice to have

Bonus contributions propose methods to introduce automated testing into workflows. Experience with tools such as Selenium, Cypress, or similar demonstrates capability in automated testing practices. Knowledge of debugging tools and methodologies adds value to verification activities.

English level B2 or better handles complex communication and documentation needs.

Practical notes

The compensation is set at 800 USD per month. Clear understanding of Github and control systems is required.

Typical interview steps

Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.

Good to know

Roles in quality assurance often combine manual exploration with structured test planning. Web application testing requires attention to detail in design and workflow validation. Familiarity with automation tools supports efficient testing at scale.

Questions to ask

Useful questions for the interview: what a typical week looks like, how work is assigned, what tools the team uses, and how feedback works. Asking how the role has changed recently and what the team wishes it had known when joining is also reasonable. Questions about the manager's priorities are especially valued.

Career growth

Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.