Senior QA Engineer – UI Automation (Python)

📍 Job Overview

Job Title: Senior QA Engineer – UI Automation (Python)

Company: Amdaris

Location: Chișinău, Moldova

Job Type: Full-Time

Category: Quality Assurance / Software Engineering

Date Posted: May 13, 2026

Experience Level: Mid-Senior Level (3-5+ years)

Remote Status: On-site

🚀 Role Summary

• Spearhead the quality assurance strategy for an innovative English Language Learning ecosystem, focusing on AI-generated, non-deterministic content.

• Own the end-to-end quality lifecycle, including workflow design, LLM orchestration, evaluation, and production operations, ensuring consistent educational standards.

• Drive the adoption of a shift-left quality model by defining testing standards and enabling developers to own unit and integration test coverage.

• Implement comprehensive testing approaches for AI/ML systems, including LLM evaluation benchmarks, regression datasets, and golden-set validation.

• Integrate automated testing into CI/CD pipelines, leveraging cloud environments (Azure/AWS) and modern DevOps practices.

📝 Enhancement Note: This role is positioned as a Senior QA Engineer with a strong emphasis on UI Automation and Python, but its scope extends significantly into AI/ML systems quality assurance and full-stack testing. The "Senior" title implies leadership in defining quality strategies and mentoring junior team members, especially concerning the unique challenges of testing non-deterministic AI outputs. The "On-site" work arrangement in Chișinău, Moldova, is a key factor for candidates considering relocation or local opportunities.

📈 Primary Responsibilities

• Define and execute comprehensive test strategies across the full stack, encompassing backend APIs (FastAPI), frontend UIs, and complex agentic workflows.

• Establish and enforce testing standards and frameworks that empower developers to maintain high unit and integration test coverage, aligning with a proactive, shift-left quality model.

• Design and implement specialized testing approaches for AI-generated content, focusing on non-deterministic outputs through LLM evaluation benchmarks, robust regression datasets, and golden-set validation.

• Lead and govern the automated testing strategy, taking ownership of end-to-end and system-level validation while actively supporting developers in crafting their unit and integration tests.

• Ensure holistic quality across the platform by implementing workflow validation that considers the interplay of text, audio, and generated content, not just individual components.

• Collaborate closely with AI engineers to meticulously define quality gates for content generation pipelines, ensuring AI outputs meet stringent educational and functional requirements.

• Conduct thorough API testing, load testing, and performance validation for all platform services to ensure scalability and reliability.

• Seamlessly integrate automated testing into CI/CD pipelines, specifically utilizing GitHub Actions within Azure and AWS environments.

• Proactively track, analyze, and report on key quality metrics across the entire platform to drive continuous improvement.

• Act as a vocal advocate for quality standards and best practices, fostering a culture of excellence across the engineering team.

📝 Enhancement Note: The responsibilities highlight a blend of traditional QA engineering with cutting-edge AI/ML testing challenges. The emphasis on "shift-left quality," "developer enablement," and "full-stack" testing suggests a collaborative environment where QA is integrated early in the development lifecycle. The specific mention of "non-deterministic AI outputs" and "LLM evaluation benchmarks" requires candidates to have experience or a strong aptitude for understanding and testing AI-driven systems.

🎓 Skills & Qualifications

Education: While no specific degree is listed, a Bachelor's degree in Computer Science, Engineering, or a related field is typically expected for a Senior QA Engineer role in this domain. Equivalent practical experience will also be highly valued.

Experience: 3–5+ years of dedicated Quality Assurance experience with a demonstrable full-stack focus, covering both backend and frontend systems.

Required Skills:

• Proficient in Python and its associated testing frameworks, with a strong emphasis on pytest.

• Solid experience with frontend testing tools such as Playwright, Cypress, or equivalent automation frameworks.

• Proven experience in testing APIs (REST, WebSocket) and understanding of microservice architectures.

• Demonstrated ability to design and implement effective test strategies specifically for AI/ML systems characterized by non-deterministic outputs.

• Hands-on experience integrating automated testing suites into CI/CD pipelines.

• Understanding of core DevOps concepts, including Docker, cloud environments (Azure/AWS), and deployment pipelines.

• Experience with performance and load testing tools and methodologies.

Preferred Skills:

• Familiarity with LLM evaluation and observability tools like Langfuse is a significant advantage.

• Daily user experience with AI development tools such as Cursor, Claude Code, or GitHub Copilot.

• Experience with Kafka or other message queuing systems for backend integration testing.

• Knowledge of database testing and SQL.

• Familiarity with Agile development methodologies and Scrum practices.

📝 Enhancement Note: The requirement for "3-5+ years" of experience positions this as a mid-to-senior level role. The emphasis on Python (pytest) and frontend tools (Playwright/Cypress) indicates a need for strong automation skills. The unique requirement to "design testing approaches for non-deterministic AI outputs" is a critical differentiator, suggesting that candidates with experience in AI/ML testing or a strong analytical aptitude for such systems will be highly sought after. The daily use of AI development tools is an interesting "nice-to-have" that signals the team's embrace of AI in their own workflows.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrable examples of automated test scripts written in Python, showcasing pytest usage and robust test case design.

• Case studies or project summaries detailing your experience with API testing (REST/WebSocket) and microservice validation.

• Evidence of UI automation frameworks developed or significantly contributed to, preferably using Playwright or Cypress.

• Documentation or project examples illustrating your ability to design and implement test strategies for complex systems, ideally including any experience with AI/ML or non-deterministic outputs.

Process Documentation:

• Showcase your approach to defining and documenting comprehensive test strategies, including test plans and test case design.

• Provide examples of how you have implemented and governed automated testing frameworks, emphasizing maintainability and scalability.

• Illustrate your methodology for tracking, analyzing, and reporting on quality metrics, demonstrating how data influences decision-making.

• Include examples of workflow validation processes you have designed or improved, particularly those involving interconnected system components.

📝 Enhancement Note: For a Senior QA Engineer role, especially one involving AI and full-stack testing, a strong portfolio is crucial. Candidates should be prepared to showcase not just code but also their strategic thinking. The emphasis on "non-deterministic AI outputs" suggests a need for portfolio pieces that demonstrate analytical problem-solving beyond standard deterministic testing. Portfolio items should highlight contributions to process improvement and the development of robust, scalable automation solutions.

💵 Compensation & Benefits

Salary Range: Based on industry benchmarks for Senior QA Engineers with 3-5+ years of experience in Eastern Europe, particularly Chisinau, and considering the specialized skills in Python automation and AI/ML testing, a competitive salary range would typically be between €2,500 - €4,000 gross per month. This estimate accounts for the company's size, international project focus, and the demand for specialized technical skills.

Benefits:

• Professional Development: Opportunities for certification and training to enhance skills.

• Workstation: Dual monitor setup and high-spec workstations provided.

• Language Development: English courses to improve communication proficiency.

• Wellness: Gym allowance and Medical Reimbursement for health and well-being.

• Financial Security: Full salary covered up to 20 days of sickness.

• Flexibility: Flexible working hours to accommodate work-life balance.

• Recognition: Loyalty scheme to reward long-term commitment.

• Engagement: Regular team-building activities, special events, and opportunities to attend conferences.

• Global Exposure: UK/EU Travel opportunities for business or team events.

• Office Amenities: Snacks and drinks available in the office.

Working Hours: The job specifies flexible working hours, typically aligning with a standard 40-hour work week, allowing for adaptability in daily scheduling while ensuring project needs are met.

📝 Enhancement Note: The salary estimation is based on aggregate data for similar roles in Moldova and the broader Eastern European tech market, factoring in the seniority and specific technical requirements (Python automation, AI/ML testing). The benefits package is comprehensive, offering a mix of professional growth, wellness, and work-life balance perks, which are attractive to tech professionals. The "Flexible working hours" are a significant benefit for operations roles, allowing for better management of testing cycles and personal commitments.

🎯 Team & Company Context

🏢 Company Culture

Industry: Software Development & IT Services, with a specific focus on delivering software solutions and joining forces with larger systems integrators like Insight. The company operates within the broader technology sector, serving clients across various industries.

Company Size: Amdaris has experienced significant growth (60% in 2021, 94% in 2022), indicating a dynamic and expanding organization. While exact current numbers aren't provided, its joining forces with Insight (a Fortune 500 company) suggests a substantial overall entity, with Amdaris likely operating as a significant division or subsidiary. This implies a company structure that balances the agility of a growing tech firm with the resources of a large corporation.

Founded: Founded in 2019, Amdaris is a relatively young but rapidly growing company. This suggests a modern, forward-thinking culture that embraces innovation and rapid evolution.

Team Structure:

• The QA team is likely integrated within cross-functional "squads" or project teams, working closely with developers, AI engineers, and product managers.

• The "Senior QA Engineer" role suggests potential for informal leadership or mentorship within the QA function on the specific project.

Methodology:

• The project emphasizes a "shift-left quality model," indicating an Agile or DevOps approach where quality is considered from the earliest stages of development.

• Data-driven decision-making is implied through the need to "track and report quality metrics."

• The use of AI agents and LLMs points towards an embrace of cutting-edge technologies and potentially experimental methodologies for content generation and validation.

Company Website: https://amdaris.com/

📝 Enhancement Note: The company culture appears to be fast-paced and growth-oriented, leveraging modern development practices and technologies. The integration with Insight provides a strong backing and potential for larger-scale projects. The emphasis on "team mentality" and "leading by example" suggests an environment where collaboration and proactive contribution are highly valued. The specific project's focus on AI and content generation indicates a team comfortable with innovation and tackling complex, non-traditional QA challenges.

📈 Career & Growth Analysis

Operations Career Level: This role is classified as a "Senior QA Engineer," indicating a mid-to-senior level position. It requires a strong foundation in QA principles, significant hands-on experience in test automation, and the ability to contribute strategically to quality initiatives. The role involves not just execution but also defining strategies, setting standards, and potentially mentoring others, especially concerning the unique challenges of AI/ML testing.

Reporting Structure: While not explicitly detailed, a Senior QA Engineer typically reports to a QA Lead, Engineering Manager, or Head of Quality Assurance. On this specific project, they will likely work within a cross-functional team, collaborating closely with developers, AI engineers, and product managers, reporting functionally within that project structure.

Operations Impact: The Senior QA Engineer plays a critical role in ensuring the quality and reliability of an AI-driven platform generating educational content. Their work directly impacts the user experience for learners, the trustworthiness of the AI outputs, and the overall success of the English Language Learning ecosystem. By defining quality gates and robust testing strategies, they mitigate risks associated with non-deterministic AI and ensure the platform meets high educational standards, thereby safeguarding the company's reputation and product integrity.

Growth Opportunities:

• Technical Specialization: Deepen expertise in AI/ML testing, LLM evaluation, and advanced automation techniques.

• Leadership Development: Opportunities to lead QA efforts on future projects, mentor junior engineers, and influence QA strategy across the organization.

• Cross-functional Exposure: Gain experience working with cutting-edge AI technologies, cloud infrastructure, and diverse development teams.

• Career Advancement: Potential progression to QA Lead, Test Architect, or Engineering Management roles within Amdaris or its parent entities.

• Continuous Learning: Access to training, certifications, and conferences to stay abreast of the latest trends in QA and AI.

📝 Enhancement Note: The growth path for a Senior QA Engineer in this context is strong, especially given the focus on AI and automation. The role offers a chance to become a subject matter expert in a rapidly evolving field. The "operations impact" is significant, as quality in an AI-driven educational platform is paramount for user trust and product success. Amdaris's growth and affiliation with Insight suggest ample opportunities for career progression and exposure to diverse projects.

🌐 Work Environment

Office Type: The job explicitly states an "On-site" work arrangement in Chișinău, Moldova. This suggests a traditional office environment designed for collaboration and team interaction.

Office Location(s): Chișinău, Moldova. Specific office details are not provided, but the mention of "office snacks and drinks" implies a dedicated, well-equipped workspace.

Workspace Context:

• Collaborative Atmosphere: The emphasis on "team mentality," "team building activities," and "collaboration" points to an office environment that fosters interaction and knowledge sharing among colleagues.

• Technological Resources: Provision of "dual monitor setup and high-spec workstations" ensures engineers have the necessary tools to perform their tasks efficiently.

• Team Interaction: Being on-site facilitates direct communication and spontaneous problem-solving with fellow QA engineers, developers, and AI specialists.

Work Schedule: The "Flexible working hours" benefit indicates that while the role is on-site, there’s an understanding of work-life balance, allowing employees some discretion in structuring their workday, provided project deliverables and team coordination needs are met.

📝 Enhancement Note: The "On-site" requirement is a key detail. Candidates must be willing and able to work from the Chișinău office. The provision of specific equipment and flexible hours suggests a supportive and modern work environment focused on productivity and employee well-being within the office setting.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or hiring manager will likely conduct an initial phone screen to assess basic qualifications, experience, and cultural fit.

• Technical Interview(s): Expect in-depth technical interviews focusing on Python programming, pytest, UI automation principles, API testing, and your approach to testing AI/ML systems. This may include live coding exercises or whiteboard problem-solving.

• Portfolio Review: A dedicated session to walk through selected projects from your portfolio. Be prepared to explain your role, the challenges faced, the solutions implemented, and the impact of your work, especially concerning process optimization and automation.

• System Design/Strategy Discussion: Questions related to designing test strategies for complex systems, particularly for non-deterministic AI outputs, and integrating testing into CI/CD pipelines.

• Manager/Team Interview: A final interview with the hiring manager and potentially key team members to evaluate leadership potential, collaboration skills, and overall fit with the team's culture and working style.

Portfolio Review Tips:

• Curate Strategically: Select projects that best demonstrate your proficiency in Python, UI automation (Playwright/Cypress), API testing, and your innovative approaches to testing AI/ML systems.

• Focus on Impact: For each project, clearly articulate the problem, your specific contribution, the technical solutions used, and quantifiable results (e.g., reduction in bugs, increase in test coverage, improvement in defect detection rates, efficiency gains).

• Highlight AI/ML Testing: If you have experience testing AI/ML or non-deterministic systems, make this a central theme. Explain your methodologies for evaluating outputs, setting quality gates, and handling variability.

• Code Quality: Ensure any code samples are clean, well-documented, and follow best practices. Be prepared to discuss your design choices.

• Process Improvement: Showcase how your QA efforts have led to process improvements, such as implementing shift-left strategies or enhancing CI/CD integration.

Challenge Preparation:

• Coding Challenges: Practice Python coding problems, focusing on algorithms, data structures, and object-oriented programming relevant to test automation. Familiarize yourself with pytest syntax and advanced features.

• Automation Scenarios: Be ready to design automation solutions for given UI or API scenarios. Think about test data management, page object models (POM), and handling dynamic elements.

• AI/ML Testing Scenarios: Prepare to discuss hypothetical scenarios for testing AI-generated content. How would you validate accuracy, relevance, and consistency? What metrics would you track?

• CI/CD Integration: Understand the principles of CI/CD and how automated tests are integrated and executed within such pipelines.

📝 Enhancement Note: The interview process is designed to thoroughly assess technical expertise, strategic thinking, and practical application of QA principles, especially in the context of AI. The portfolio review is a critical component, requiring candidates to present tangible evidence of their skills and impact. Preparation should focus on demonstrating not just what was done, but why and how, with a clear emphasis on the unique challenges of this role.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Language: Python (essential for automation and backend testing).

• Python Testing Framework: pytest (core requirement for test development).

• Frontend Automation: Playwright, Cypress, or equivalent tools for UI test automation.

• Backend API Testing: Tools and techniques for testing REST and WebSocket APIs.

• AI Development Tools: Daily use of tools like Cursor, Claude Code, or GitHub Copilot is preferred.

Analytics & Reporting:

• CI/CD Platforms: GitHub Actions for integrating automated tests into the development pipeline.

• Cloud Environments: Azure and AWS for deployment and testing infrastructure.

• Observability Tools: Familiarity with LLM evaluation and observability tools like Langfuse is a strong plus.

• Performance & Load Testing: Tools for conducting performance and load validation.

CRM & Automation:

• Containerization: Docker for environment consistency and deployment.

• Microservices Architecture: Understanding and testing principles within a microservices environment.

• Version Control: Git (implied by GitHub Actions).

📝 Enhancement Note: Proficiency in Python and pytest is non-negotiable. Experience with Playwright or Cypress is also key for UI automation. The role leans heavily into modern DevOps, cloud (Azure/AWS), and CI/CD practices, with GitHub Actions being specified. The preference for familiarity with AI observability tools like Langfuse and daily use of AI coding assistants highlights the team's cutting-edge technological focus.

👥 Team Culture & Values

Operations Values:

• Quality First: A strong commitment to delivering high-quality, reliable software, with a particular focus on the nuances of AI-generated content.

• Innovation & Agility: Embracing new technologies (AI/ML) and methodologies (shift-left, CI/CD) to drive efficiency and product excellence.

• Collaboration & Teamwork: Fostering a supportive environment where team members work together, share knowledge, and "lead by example" to achieve common goals.

• Continuous Improvement: A dedication to ongoing learning, process optimization, and proactively identifying and addressing quality challenges.

• Data-Driven Decisions: Utilizing metrics and analysis to inform quality strategies and track progress.

Collaboration Style:

• Cross-functional Integration: Close collaboration with developers, AI engineers, and product managers is essential, working within integrated teams.

• Mentorship & Knowledge Sharing: Encouraging senior members to guide and support junior colleagues, and promoting open sharing of best practices and learnings.

• Proactive Communication: Maintaining clear and consistent communication channels, especially regarding test strategies, findings, and potential risks.

• Feedback Loop: Openness to constructive feedback and a willingness to adapt approaches based on team input and project evolution.

📝 Enhancement Note: The culture emphasizes a proactive, collaborative, and technically forward-thinking approach to quality assurance. The values align with modern software development practices, with a unique emphasis on handling the complexities of AI. Candidates should demonstrate an ability to thrive in a dynamic, growth-oriented environment that values both individual contribution and collective success.

⚡ Challenges & Growth Opportunities

Challenges:

• Testing Non-Deterministic AI: The primary challenge is devising effective test strategies for AI-generated content that is inherently variable and non-deterministic. This requires moving beyond traditional QA methodologies.

• Maintaining Quality at Scale: Ensuring consistent quality across a large-scale English Language Learning ecosystem with AI-driven content generation presents significant scalability challenges.

• Integrating Diverse Technologies: Effectively testing a full-stack platform that combines backend APIs, frontend UIs, and sophisticated AI agentic workflows requires broad technical understanding.

• Balancing Speed and Rigor: Adhering to a "shift-left quality model" and CI/CD integration while maintaining the necessary rigor for educationally consequential content requires careful process design and automation.

Learning & Development Opportunities:

• AI/ML Testing Specialization: Become an expert in the emerging field of AI/ML quality assurance, including LLM evaluation techniques and observability tools.

• Advanced Automation Skills: Deepen expertise in Python-based automation, potentially exploring new frameworks or advanced testing patterns.

• Cloud & DevOps Mastery: Gain hands-on experience with Azure and AWS, and further develop skills in CI/CD pipeline automation.

• Cross-Functional Leadership: Develop leadership capabilities through mentoring, strategy definition, and influencing quality practices across project teams.

• Industry Exposure: Attend conferences and participate in training programs related to AI, software testing, and cloud technologies.

📝 Enhancement Note: This role offers the opportunity to tackle some of the most cutting-edge challenges in software quality assurance. The growth potential is significant for individuals who can adapt to and excel in testing AI-driven systems, positioning them at the forefront of QA innovation.

💡 Interview Preparation

Strategy Questions:

• "How would you design a test strategy for an AI system that generates non-deterministic content, specifically for an educational platform? What metrics would you prioritize?" Focus on defining quality gates, potential evaluation benchmarks, and how to handle variability.

• "Describe your experience integrating automated testing into CI/CD pipelines. Can you walk me through a specific example using GitHub Actions, Azure, or AWS?" Be ready to explain the setup, challenges, and benefits.

Company & Culture Questions:

• "Why are you interested in working with AI-generated content and testing non-deterministic outputs?" Show genuine curiosity and understanding of the unique challenges.

• "How do you foster a 'quality-first' culture within a development team, especially when working on a fast-paced, agile project?" Discuss your approach to advocacy, collaboration, and mentorship.

Portfolio Presentation Strategy:

• Structure Your Narrative: For each portfolio piece, clearly outline the context (project goal), your specific role and contributions, the technical challenges (especially AI-related), the automation solutions you implemented (Python, pytest, Playwright), and the measurable impact on quality or efficiency.

• Showcase AI/ML Testing: If applicable, dedicate time to explaining your methodology for testing AI outputs. Discuss how you defined success criteria, handled variability, and ensured educational relevance.

• Demonstrate Technical Depth: Be ready to discuss the technical details of your automation frameworks, CI/CD integrations, and API testing approaches. Explain your design choices and why you selected specific tools or patterns.

• Focus on Process Improvement: Highlight instances where your work led to improvements in the overall QA process, such as enhancing test coverage, reducing regression bugs, or enabling faster feedback loops through automation.

📝 Enhancement Note: Preparation should focus on demonstrating a deep understanding of QA principles, strong technical automation skills, and a unique ability to tackle the complexities of AI/ML testing. The interview will likely probe not just technical ability but also strategic thinking and problem-solving skills relevant to the specific project context.

📌 Application Steps

To apply for this Senior QA Engineer position:

• Submit your application through the provided link on the Amdaris careers page.

• Portfolio Customization: Tailor your resume and cover letter to highlight your experience with Python, pytest, UI automation (Playwright/Cypress), API testing, and any direct experience or relevant skills in testing AI/ML systems or non-deterministic outputs.

• Resume Optimization: Ensure your resume clearly outlines your 3-5+ years of QA experience, focusing on achievements and quantifiable results rather than just responsibilities. Use keywords from the job description, such as "UI Automation," "Python," "pytest," "AI/ML," "CI/CD," and "full-stack testing."

• Interview Preparation: Thoroughly review the "Interview Preparation" section above. Practice articulating your experience with the STAR method, prepare specific examples for strategy and behavioral questions, and be ready to present key projects from your portfolio.

• Company Research: Familiarize yourself with Amdaris's mission, recent growth, and its partnership with Insight. Understand their approach to software development and their commitment to quality. This will help you tailor your responses to demonstrate cultural fit and strategic alignment.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.