Job
Description
As a Senior QA Engineer at our company, you will play a crucial role in leading quality initiatives for our AI-powered supply chain forecasting and decision platforms. You will leverage cutting-edge AI tools and automation to build intelligent testing systems that validate complex ML models, data pipelines, and distributed systems. Your focus will be on ensuring our platforms deliver accurate, reliable results at scale. **Key Responsibilities:** - **AI-Focused Test Automation** - Build intelligent test automation frameworks using tools like Playwright MCP - Implement automated validation for ML model outputs, forecast accuracy, and data pipeline integrity - Design performance and testing strategies for distributed systems and concurrent workflows - Create smart test selection to optimize regression suite execution based on code changes - **Quality Strategy & Architecture** - Own end-to-end quality strategy across microservices architecture and data platforms - Embed quality gates throughout CI/CD pipelines and enforce shift-left practices - Build frameworks for testing event-driven architectures, async workflows, and agent-based systems - Define, track, and publish quality metrics including test coverage and defect escape rate - **Data & ML Quality Assurance** - Develop automated validation for ETL processes, data transformations, and feature engineering pipelines - Build testing strategies for orchestrated workflows and batch processing systems - Implement data quality checks across ingestion, processing, and serving layers **Required Qualifications:** - 5+ years in QA/SDET roles with 2+ years testing data-intensive or ML products - Strong programming skills in Python and JavaScript/TypeScript - Hands-on experience with modern AI tools and test automation frameworks - Experience in testing microservices, distributed systems, and cloud-native applications - Understanding of data engineering workflows, CI/CD pipelines, and infrastructure as code **Preferred Qualifications:** - Knowledge of data orchestration platforms and ML model validation techniques - Experience testing data processing systems - Background in supply chain, forecasting, or optimization domains In this role, you will work with a tech stack including Backend (FastAPI, Python, PostgreSQL), Frontend (React, TypeScript), Data & ML (Databricks, Dagster, MLflow), Infrastructure (AWS, Docker, Kubernetes), CI/CD (Azure DevOps), and Monitoring (Datadog). This role is unique as you will architect quality systems that use AI to test AI-powered platforms. You will have the autonomy to research and implement next-generation testing tools while directly impacting product reliability and customer satisfaction. Join us to transform quality practices, build self-improving test systems, enable rapid deployments, and establish quality as a competitive advantage in the AI supply chain space.,
