Lead QA Engineer (AI native)
Role Overview
This position is listed on behalf of a partner company, who manages all applications and next steps.
The partner is looking for a Lead QA Engineer (AI Native) based in United Arab Emirates.
Join a small, senior engineering team building a product in an AI-first development environment.
You will take ownership of the quality strategy for a complex codebase where AI agents generate most of the code.
The product includes critical financial flows, making reliability, testing, and release safety central to the role.
You will design the end-to-end testing pipeline, from pre-merge validation through release and production gates.
The role combines hands-on test automation, engineering, AI-agent workflows, and continuous quality improvement.
As an individual contributor in a flat team, your impact will come through automation, scalable processes, and intelligent use of AI.
You will have substantial autonomy to define how quality is managed in an evolving AI-native engineering environment.
Key Skills for This Role
Full Job Posting
Role Overview
This position is listed on behalf of a partner company, who manages all applications and next steps.
The partner is looking for a Lead QA Engineer (AI Native) based in United Arab Emirates.
Join a small, senior engineering team building a product in an AI-first development environment.
You will take ownership of the quality strategy for a complex codebase where AI agents generate most of the code.
The product includes critical financial flows, making reliability, testing, and release safety central to the role.
You will design the end-to-end testing pipeline, from pre-merge validation through release and production gates.
The role combines hands-on test automation, engineering, AI-agent workflows, and continuous quality improvement.
As an individual contributor in a flat team, your impact will come through automation, scalable processes, and intelligent use of AI.
You will have substantial autonomy to define how quality is managed in an evolving AI-native engineering environment.
Accountabilities
- Design and build the end-to-end testing pipeline, including pre-merge checks, nightly test runs, release validation, and production quality gates.
- Define the quality strategy for AI-generated code, identifying high-risk areas, establishing appropriate test coverage, and ensuring the approach remains sustainable as the product scales.
- Build and maintain continuous automated UI testing across browsers and mobile devices, including AI-agent-driven testing approaches.
- Evaluate, select, and integrate external testing tools and services where they can improve reliability, coverage, or efficiency.
- Own product reliability from a technical QA perspective, with particular attention to critical financial workflows.
- Collaborate closely with engineering and DevOps teams to embed quality throughout the development lifecycle and balance delivery speed with appropriate safeguards.
- Use AI coding agents such as Claude Code, Codex, Cursor, or similar tools on a daily basis to create, maintain, and evolve testing solutions.
- Proactively identify quality risks, introduce improvements, and share testing practices and knowledge across the team.
Requirements
- Proven experience designing and owning testing processes for large, complex products with high reliability requirements, such as in a QA Architect, Senior QA/SDET, or senior engineering role with responsibility for testing strategy.
- Strong software engineering foundation, including a solid understanding of system architecture, backend services, CI/CD pipelines, and deployment processes.
- Hands-on experience building automated tests and integrating testing into CI/CD workflows.
- Practical daily experience using AI coding agents such as Claude Code, Codex, Cursor, or comparable tools as an integral part of software development.
- Genuine interest in AI-first development and the ability to adapt testing practices to AI-generated code.
- Strong autonomy and ownership, with the ability to take loosely defined challenges, develop solutions, and drive them through implementation without detailed specifications.
- Ability and willingness to remain hands-on as an individual contributor within a small, senior-level team.
- Strong problem-solving, communication, and collaboration skills.
- Fluent Russian.
Benefits
- Fully remote, full-time opportunity.
- Initial pay level or salary range shared with candidates during the recruitment process and before employment begins.
- 28 calendar days of vacation per year.
- 7 wellness days per year that can be used for personal matters, rest, or recovery without taking sick leave.
- Referral bonuses of up to $5,000 for successful candidate recommendations.
- 50% reimbursement for professional training, international conferences, and professional meetings.
- Corporate discounts for English lessons.
- Health benefits, including reimbursement of up to $1,000 gross per year per employee where corporate medical insurance is not available.
- Workplace support, including equipment and workplace essentials in offices or coworking locations, with reimbursement of up to $1,000 gross once every three years for coworking costs or home-office equipment.
- Internal gamified recognition system where colleagues can award bonuses exchangeable for merchandise, team-building activities, massage certificates, and other rewards.
- Opportunity to work within a small, experienced, and highly autonomous engineering team focused on AI-first development.
How Jobgether Works
- Jobgether uses an AI-powered matching process to review applications quickly, objectively, and fairly against the role's core requirements.
- The system identifies top-fitting candidates, and this shortlist is shared directly with the hiring company.
- The final decision and next steps (interviews, assessments) are managed by the hiring company's internal team.
- By submitting an application, candidates acknowledge that Jobgether will process personal data to evaluate candidacy and share relevant information with the hiring employer.
- AI tools may be used to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses; final hiring decisions are made by humans.
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