Lead QA IT Engineer

Key Responsibilities

• Lead QA strategy and define testing approaches for agentic AI systems and ML applications
• Design and implement comprehensive test automation frameworks using Python
• Develop specialized testing methodologies for AI models including accuracy, fairness, robustness, and drift detection
• Build and maintain CI/CD pipelines with integrated automated testing
• Test complex Azure architectures including microservices, serverless functions, and distributed systems
• Validate data pipelines, ETL processes, and analytics workflows in Azure Databricks
• Perform advanced performance testing, load testing, and scalability validation
• Establish quality metrics, KPIs, and reporting dashboards for AI applications
• Mentor junior QA engineers and promote best practices across the team
• Collaborate with architects and developers on testability and quality requirements
• Implement monitoring and validation strategies for production AI systems
• Lead root cause analysis for critical production issues
• Evaluate and integrate new testing tools and frameworks
• Ensure compliance with security, privacy, and regulatory requirements

Required Skills & Qualifications

QA Leadership:

• 8+ years of experience in software QA with at least 2+ years testing AI/ML systems
• Proven track record of establishing QA processes and testing frameworks
• Experience leading testing efforts for production-grade applications
• Strong understanding of QA best practices, methodologies, and industry standards

Use LLM or AI for testing or Python working experience in testing.

Technical Expertise:

• Expert-level proficiency in Python for test automation and scripting
• Advanced SQL skills for complex data validation and quality checks
• Deep knowledge of Azure services (Functions, ML, OpenAI, Databricks, Storage, API Management)
• Extensive hands-on experience with Azure Databricks including testing data workflows
• Strong experience building and maintaining CI/CD pipelines (Azure DevOps, GitHub Actions)
• Proficiency with test automation frameworks (pytest etc...)
• Experience with API testing and microservices validation

AI/ML Testing Expertise:

• Strong understanding of Machine Learning, Natural Language Processing, and Deep Learning
• Specialized knowledge of AI/ML testing strategies (model evaluation, data quality, bias detection, adversarial testing)
• Experience testing LLM-based applications including prompt validation and response quality
• Knowledge of MLOps practices and testing ML pipelines
• Understanding of A/B testing and experimentation frameworks
• Familiarity with model monitoring and drift detection

Azure & Databricks:

• Deep knowledge of Azure architecture and deployment patterns
• Experience testing serverless applications and event-driven systems
• Proficiency with Azure monitoring tools (Application Insights, Log Analytics)
• Strong understanding of Databricks notebooks, jobs, and cluster configurations
• Experience with infrastructure testing and validation

Problem-Solving & Quality:

• Exceptional analytical and debugging skills
• Experience with performance testing tools.
• Knowledge of security testing principles and tools
• Strong understanding of observability and monitoring strategies

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related field
• Azure certifications (Azure Administrator, Azure Solutions Architect)
• Databricks certification (Spark Developer, ML Associate)
• Experience with resilience testing
• Experience testing multi-agent systems or autonomous AI applications
• Familiarity with MLflow, Azure ML, or other MLOps platforms
• Experience with test data management and synthetic data generation

Nuestro compromiso con una cultura de inclusión y pertenencia
Ecolab está comprometido con el trato justo e igualitario de todas las personas colaboradoras y postulantes, y con la promoción de los principios de igualdad de oportunidades en el empleo. Reclutaremos, contrataremos, promoveremos, transferiremos y brindaremos oportunidades de desarrollo con base en las calificaciones individuales y el desempeño laboral, en todos los aspectos relacionados con el empleo, la compensación, los beneficios, las condiciones laborales y las oportunidades de crecimiento. Ecolab no discriminará a ninguna persona colaboradora ni postulante por motivos de raza, religión, color, credo, nacionalidad, estado de ciudadanía, sexo, orientación sexual, identidad y expresión de género, información genética, estado civil, edad o discapacidad.