Senior Artificial Intelligence Quality Engineer

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Create workflows for AI test orchestration.

• Develop and utilize AI harnesses.

• Assess AI-generated quality architectures at the portfolio level.

• Architect, write, and sustain automated tests throughout the stack.

• Design and implement quality assurance for distributed systems or enterprise-scale applications.

• Conduct non-functional testing focusing on performance, security, accessibility, and reliability.

• Develop AI-enhanced Agile quality workflows.

• Establish AI quality governance frameworks.

• Build testing frameworks and quality gates for AI-generated code.

• Act as the quality engineering lead for a solutions team.

• Offer technical leadership and strategic influence in quality engineering.

⛳️ Requirements

• Proven capability to design workflows for AI test orchestration and AI harnesses, along with validating AI-generated quality architectures at the portfolio level.

• In-depth understanding of AI test orchestration platforms, multi-agent test system architecture, test context engineering, AI harnesses, and the strengths and limitations of AI-driven testing.

• Extensive commercial experience in quality engineering, demonstrating a successful history of technical leadership and strategic influence.

• Strong grasp of test architecture patterns and a comprehensive perspective on quality at the portfolio level.

• Practical experience in designing, writing, and maintaining automated tests across the stack.

• Background in designing and executing quality assurance for distributed systems or enterprise-scale applications.

• Experience with enterprise-level non-functional testing, including performance, security, accessibility, and reliability.

• Familiarity with designing AI-augmented Agile quality workflows and AI quality governance frameworks.

• Proficiency in at least one modern backend programming language, such as Java, Python, or TypeScript/Node.js.

• Experience with cloud platforms, such as AWS.

• Knowledge of CI/CD tools, like Jenkins or Bitbucket Pipelines.

• Familiarity with containerization technologies, such as Docker or Kubernetes.

• Broad understanding across the technology stack.

• Practical knowledge of AI coding/testing assistants, AI code review tools, and multi-agent orchestration frameworks.

• Experience in creating testing frameworks and quality gates for AI-generated code at the portfolio level.

• Previous role as the quality engineering lead for a solutions team.

• Bachelor's degree or equivalent education in Computer Science, Mathematics, Chemistry, or a related field.

• Exceptional commercial experience leading quality engineering at the system or portfolio level may substitute for the degree requirement.

• Professional software testing certification, such as ISTQB Advanced or Expert, is preferred.

• Experience in testing software products within a scientific domain is preferred.

• Experience with performance management and people management in a matrixed environment is preferred.

🏝️ Benefits

• The support you need to achieve professional success.

• A collaborative and innovative environment.