QA Automation Engineer

About Us
Zovi is a boutique AI strategy and technology consulting firm. We help growth-stage companies and enterprise teams build with AI — from strategy through to shipped product. Our work spans AI strategy and roadmapping, custom AI development (RAG pipelines, agentic workflows, and Azure OpenAI & Anthropic integrations built in .NET and Python), data platform and analytics (Databricks, Snowflake, dbt, Power BI), technology due diligence, fractional CTO and AI leadership, and AI enablement and training.
We are looking for an experienced QA Automation Engineer with strong automation expertise and Upper C1 level English communication skills to join our global remote team and help us strengthen software quality across our client engagements, AI products, and data platforms.
In this role, you will design, develop, and maintain automated testing frameworks, validate the functionality and reliability of AI-driven and data-heavy applications, improve test coverage, and clearly communicate quality risks, defects, test results, and release readiness to engineering, product, and client stakeholders. You will work closely with cross-functional teams and clients in English to clarify requirements, explain technical issues in simple business terms, support smooth and stable releases, improve testing efficiency, reduce manual effort, and help our teams deliver better software faster.

Responsibilities
Test Automation Development: Design, build, and maintain automated test scripts and test frameworks for web applications, APIs, backend services, AI/LLM-powered features, and data-driven workflows.
Test Planning & Strategy: Create clear test plans, test cases, and test strategies based on product requirements, user stories, acceptance criteria, and client business priorities.
Functional & Regression Testing: Execute automated functional, regression, smoke, integration, and end-to-end tests to ensure application stability across releases.
API Testing: Validate REST APIs and backend services using tools such as Postman, REST Assured, Playwright API testing, or similar frameworks.
UI Automation: Build and maintain UI automation tests using tools such as Selenium, Playwright, Cypress, or similar automation frameworks.
CI/CD Integration: Integrate automated tests into CI/CD pipelines using tools such as Jenkins, GitHub Actions, GitLab CI, Azure DevOps, or similar platforms.
Defect Management: Identify, document, track, and verify software defects using tools such as Jira, Azure DevOps, or similar issue-tracking systems.
Collaboration: Work closely with developers, product managers, business analysts, consultants, and other QA team members to understand requirements and ensure test coverage aligns with client and business needs.
Test Coverage Improvement: Analyze gaps in current testing coverage and continuously improve automation scope, test reliability, and execution speed.
Data Validation: Perform database and data validation testing using SQL to ensure data accuracy, consistency, and integrity across systems and data platforms (e.g., Snowflake, Databricks).
AI & Data Pipeline Quality: Support quality validation of RAG pipelines, agentic workflows, and analytics/BI outputs, including evaluation of model-driven behavior where applicable.
Performance & Reliability Support: Support basic performance, load, and reliability testing when needed to help identify system bottlenecks and quality risks.
Reporting & Documentation: Create clear test reports, defect summaries, release quality updates, and testing documentation for technical and non-technical stakeholders.
Automation Optimization: Improve existing automation scripts by reducing flaky tests, increasing reusability, and applying best practices in test design.
Quality Advocacy: Promote a quality-first mindset across the team and help improve QA processes, release readiness, and software delivery standards.

Requirements
Communication: Excellent communication skills, specifically fluent verbal English, are mandatory to explain testing results, quality risks, and technical issues to both technical and non-technical stakeholders, including clients.
Education: Bachelor's degree in Computer Science, Information Technology, Software Engineering, or a related field, or equivalent practical experience.
Experience: Proven experience as a QA Automation Engineer, Software Test Engineer, SDET, or similar role with hands-on automation testing experience.
Programming: Strong programming or scripting skills in one or more languages such as Python, C#/.NET, JavaScript, TypeScript, or Java.
Automation Tools: Hands-on experience with automation frameworks such as Selenium, Playwright, Cypress, TestNG, JUnit, PyTest, or similar tools.
API Testing: Strong experience testing REST APIs using Postman, REST Assured, Playwright, or similar tools.
SQL & Data Validation: Good understanding of SQL for validating data, writing queries, and checking backend/database behavior.
Testing Fundamentals: Strong understanding of software testing concepts, including functional testing, regression testing, integration testing, smoke testing, UAT, and end-to-end testing.
CI/CD: Experience integrating automated tests into CI/CD pipelines and working with version control systems such as Git.
Agile Environment: Experience working in Agile or Scrum teams, participating in sprint planning, backlog refinement, daily standups, and release cycles.
Defect Tracking: Experience using Jira, Azure DevOps, TestRail, Zephyr, or similar tools for test case management and defect tracking.
Problem Solving: Strong analytical and problem-solving skills with the ability to troubleshoot test failures, isolate root causes, and communicate issues clearly.
Attention to Detail: Strong attention to detail and a quality-focused mindset to ensure software meets functional, business, and user experience expectations.

Preferred Qualifications
Advanced Automation Frameworks: Experience designing reusable, scalable, and maintainable automation frameworks from scratch.
Cloud Platforms: Familiarity with cloud environments such as Azure, AWS, or Google Cloud for testing cloud-hosted applications.
AI Integrations: Familiarity testing applications built on Azure OpenAI, Anthropic, or similar LLM providers, including RAG and agentic workflows.
Data Platform & Analytics: Experience testing data pipelines, ETL/dbt workflows, and BI outputs across platforms such as Databricks, Snowflake, or Power BI.
Containerization: Basic understanding of Docker, Kubernetes, or containerized test environments.
Performance Testing: Familiarity with performance testing tools such as JMeter, k6, Gatling, or similar tools.
Security Testing Awareness: Basic knowledge of security testing concepts, authentication flows, authorization checks, and common web vulnerabilities.
Mobile Testing: Experience with mobile test automation tools such as Appium or similar frameworks.
Test Reporting: Experience building dashboards or reports to track test coverage, automation pass rate, defect trends, and release quality.
AI-Assisted Testing: Familiarity with AI-assisted testing tools, test generation, self-healing tests, evaluation frameworks, or intelligent test automation is a plus.
Business Acumen: Ability to understand client business goals and align testing priorities with product quality, customer experience, and delivery timelines.

Why Zovi?
Competitive salary and flexible payment methods.
Opportunities for growth and professional development at the frontier of AI consulting.
Flexible working hours and fully remote work options.
A collaborative, innovative, and inclusive work environment.
Be part of a quality-driven culture that values reliable software, continuous improvement, and strong engineering practices.
Work with cross-functional teams and clients to improve product quality, automation coverage, and release confidence across AI and data-driven products.