Quality Engineer – AI, Software, & Automation Solutions

Location: Remote - Brazil

Department: Engineering

Location Type: REMOTE

Employment Type: FULL_TIME

• Develop QMS (Quality Management Systems) framework for internal and external solutions.
• Develop comprehensive test plans across front-end, backend, automation, and AI layers.
• Validate application logic, agent workflows, API integrations, prompt quality, and error handling.
• Test AI agent behavior for reliability, consistency, safety guardrails, and edge case scenarios.
• Build automated test suites where appropriate using modern frameworks and AI tools.
• Evaluate human-in-the-loop workflows, reasoning path visibility, and agent state transitions.

• Create internal automation tools that support quality checks, regression testing, and consistency validation.
• Build utilities that monitor AI output correctness and detect drift or prompt failure patterns.
• Implement automated validation for large-scale workflows such as n8n, custom automations, and model-driven tasks.
• Design intelligent alerting systems that surface issues early in the development cycle.

• Use AI coding platforms to improve velocity and maintain high quality in test development.
• Build LLM-assisted testing scripts and automated evaluation harnesses for generative AI features.
• Work with engineering to integrate AI into QA processes such as automated prompt scoring and conversational flow validation.
• Contribute to the refinement of prompts, agent instructions, and reasoning frameworks from an accuracy and reliability perspective.

• Partner with engineering to define acceptance criteria and ensure all work is testable and observable.
• Coordinate closely with the engagement manager to ensure project readiness and identify risks before client delivery.
• Communicate test findings clearly with actionable remediation guidance.
• Serve as the final technical quality gate on all deliverables.

• Establish Dry Ground AI’s QA standards and continuously improve them as we scale.
• Create reusable testing templates and systems for use across all client projects.
• Analyze recurring issues and lead efforts to resolve root causes.
• Drive a culture of technical excellence and reliability throughout the engineering team.

• 5 or more years in a highly technical QA, SDET, or full-stack engineering role.
• Strong engineering fundamentals across JavaScript, TypeScript, Python, React, and API driven applications.
• Experience testing AI-enabled products, conversational interfaces, or complex automation workflows.
• Ability to build automated testing systems using tools such as Playwright, Cypress, or custom frameworks.
• Experience with AI-enhanced development tools such as Claude Code & Github.
• Strong understanding of prompt behavior, LLM variability, and common failure patterns.
• Comfort working across the entire stack, including cloud services, APIs, vector databases, and real-time systems.
• Excellent communication skills for coordinating across engineering and client-facing teams.

• Experience with agentic AI frameworks, voice AI systems, or workflow automation tools such as n8n.
• Experience implementing testing strategies for RAG systems, embedding workflows, and vector search pipelines.
• Familiarity with CI pipelines that run automated quality checks and AI-based evaluation tests.
• Experience in consulting environments with direct ownership of client-facing deliverables.

• Competitive compensation and performance incentives.
• Remote-first work environment.
• Opportunity to influence the architecture, reliability, and technical quality of AI systems across multiple industries.
• A culture that prioritizes innovation, high standards, and the use of AI to scale operations.