Senior QA Engineer

Senior QA Engineer

About the Role

We're seeking a Senior QA Engineer to lead quality initiatives for our AI-powered supply chain forecasting and decision platforms. This is a strategic role where you'll leverage cutting-edge AI tools and automation to build intelligent testing systems that validate complex ML models, data pipelines, and distributed systems. You'll drive our shift-left quality practices while ensuring our platforms deliver accurate, reliable results at scale.

Prediction Platform : A data centric, domain specific, model agnostic platform built especially for supply chain practitioners to generate accurate predictions.

Decision System : A supply chain planning decision system purpose built to combine the computational power of AI predictions with human judgement for enabling enterprise adoption and continuous improvement of decision quality, speed and confidence.

Key Responsibilities

AI-Focused Test Automation

• Build intelligent test automation frameworks that leverage AI for test generation, maintenance, and self-healing capabilities (using tools like Playwright MCP)
• Implement automated validation for Daybreak's ML model outputs, forecast accuracy, and data pipeline integrity
• Design performance and testing strategies for distributed systems and concurrent workflows
• Create smart test selection that 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 at the feature branch level
• Build frameworks for testing event-driven architectures, async workflows, and agent-based systems
• Define, track and publish quality metrics including test coverage, defect escape rate, and mean time to recovery

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 using modern AI tools (Claude Code, Windsurf, Playwright MCP, etc.)
• Hands-on experience with modern test automation frameworks (Playwright, Cypress, Selenium, etc.)
• Experience with performance testing tools (Locust, K6, JMeter) and API testing frameworks
• Background 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 (Dagster, Airflow, Databricks)
• Familiarity with ML platforms and model validation techniques (prepare datasets, validate model-driven test scenarios)
• Experience testing data processing systems
• Background in supply chain, forecasting, or optimization domains

Tech Stack You'll Work With

• Backend: FastAPI, Python, PostgreSQL, PydanticAI
• Frontend: React, TypeScript
• Data & ML: Databricks, Dagster, MLflow
• Infrastructure: AWS (EKS, RDS, S3), Docker, Kubernetes
• CI/CD: Azure DevOps
• Monitoring: Datadog and modern observability tools

What Makes This Role Unique

You will architect quality systems that use AI to test AI-powered platforms. This is a hands-on strategic role where you'll revolutionize how we approach quality through intelligent automation, predictive analytics, and data-driven testing strategies. You'll have the autonomy to research and implement next-generation testing tools while directly impacting product reliability and customer satisfaction.

Impact You'll Have

• Transform quality practices from reactive testing to proactive prevention
• Build self-improving test systems that learn from failures and adapt to changes
• Enable rapid, confident deployments through intelligent automation
• Establish quality as a competitive advantage in the AI supply chain space