3Cloud - Lead Consultant - Quality Engineering
Requirements
• Bachelor’s degree in computer science, or a closely related discipline. • Extensive experience in QA methodologies, test planning, automation, and quality engineering practices. • Strong proficiency in automation tools such as Selenium, Playwright, or equivalent frameworks. • Solid programming skills in Python, C#, Java, or similar languages. • Hands‑on experience testing data pipelines, ETL workflows, and analytics platforms (Databricks, Fabric preferred). • Understanding of machine learning principles, model evaluation metrics and AI system behavior • Ability to test LLM behavior, prompts, and AI model outputs. • Ability to execute comprehensive test plans for AI models and systems. • Excellent analytical, problem‑solving, communication, and presentation skills. • Demonstrated ability to work cross‑functionally and influence engineering teams. • Passion for innovation, continuous learning, and staying current with emerging QE and AI technologies. • Relevant certifications (Azure, Microsoft, Agile, etc.) are a plus. • Experience with cloud platforms, especially Azure, is preferred. • Full-time employment • 📌 Remote in Philippines • Don’t meet every single requirement? At 3Cloud we are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. • At this time, we cannot sponsor applicants for work visas.
Responsibilities
• Drive high‑quality delivery by performing both manual and automated testing, ensuring full coverage across functional, system, data, and AI components. • Lead the design and implementation of comprehensive test strategies, quality processes, and documentation for assigned project. • Maintain accurate record results, test cases, and share feedback to the project team • Ensure all QE deliverables meet quality standards, aligning with project objectives and organizational best practices. • Lead defect triage process • Develop and validate test data, data pipelines, and infrastructure from both functional and system perspectives. • Evaluate and test machine learning models, including LLM behavior, prompt robustness, model outputs, and performance metrics. • Mentor junior team members, promote QE best practices, and contribute to continuous improvement initiatives across the Quality engineering practice.
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