Staff Quality Engineer – AI-Driven Software Systems (AI)

TL;DR

Staff Quality Engineer (AI): Building intelligent systems for end-to-end test generation, legacy test-suite optimization, and automated failure triaging with an accent on integrating artificial intelligence into the software development lifecycle (SDLC) . Focus on shaping the future of software quality through AI-driven operations, combining research-level thinking with enterprise-grade engineering.

Location: Must be based in Yerevan, Armenia

Company

hirify.global is a global technology leader that designs, develops and supplies a broad range of semiconductor and infrastructure software solutions.

What you will do

• Design and implement testing frameworks that use AI for intelligent test generation, automated failure classification, and optimizing regression suites.
• Lead feature delivery from day one, ensuring rigorous end-to-end validation so the final product meets customer needs and quality standards.
• Collaborate with developers and architects to integrate AI-driven quality gates and validation steps into the CI/CD pipeline.
• Maintain automation frameworks and design experiments to ensure both the testing tools and the product remain stable and reliable.
• Research and prototype emerging AI tools (LLMs, code intelligence, autonomous agents) to accelerate complex testing workflows.
• Lead technical discussions, mentor peers, and present data-driven health and performance metrics to engineering leadership.

Requirements

• Bachelor’s degree in Computer Science or related field and 8+ years of related experience, or Master’s degree and 6+ years of related experience.
• Proven background in software development and quality engineering, with a focus on automation and data-driven testing.
• Proficient programming skills in Python or Java; experience with AI/ML frameworks is a plus.
• Experience integrating automation or analytics into CI/CD environments (e.g., Jenkins, GitHub Actions, or similar).
• Familiarity with machine learning concepts, data preparation, and evaluation metrics.
• Strong understanding of OS fundamentals, APIs, and distributed systems.

Culture & Benefits

• Values innovation, autonomy, and measurable impact.
• The team is collaborative and research-driven, combining system-level quality expertise with modern AI experimentation.
• Encouraged to challenge conventions, introduce new tools, and drive AI adoption across the broader engineering organization.