AI Senior Test Engineer

AI Senior Test Engineer

We are seeking an AI Test Lead/Senior Test Engineer for test planning and end-to-end testing of cloud-based, data-driven AI Ops platform. The role requires strong expertise in testing, automation, AI/ML, data validation, and cloud services (AWS preferred). He/she will play a pivotal role in ensuring data quality, workflow reliability, automation robustness, and AI model accuracy, working across engineering, data science, and operations teams.

Key Responsibilities:

• Test planning, test case development, and test execution covering data ingestion, pipelines, workflows, AI models, and cloud deployments.
• Establish testing methodologies for data quality, workflow orchestration, model validation, and system integrations.
• Drive adoption of automation-first testing approaches across CI/CD pipelines.
• Define validation frameworks for structured, semi-structured, and unstructured data.
• Implement checks for data integrity, transformations, schema compliance, lineage, and reconciliation.
• Test workflow orchestration (e.g., Airflow, Step Functions, Lambda, EventBridge).
• Collaborate with data science teams to design model validation tests (accuracy, bias, drift, fairness, performance).
• Automate AI model regression testing and monitoring in production environments.
• Architect test automation frameworks for data and AI pipelines.
• Build synthetic data generation strategies for testing AI/ML use cases.
• Integrate testing into DevOps/MLOps pipelines for continuous quality validation.
• Leverage AWS services (S3, Glue, Athena, Redshift, SageMaker, Step Functions, Lambda, CloudWatch, etc.) in testing frameworks.
• Ensure performance, scalability, security, and compliance testing of cloud-native solutions.
• Design failover, recovery, and resilience tests for critical workflows.
• Define quality KPIs and dashboards for data and AI testing outcomes.

Key Skills & Qualifications:

• Strong foundation in software testing principles, test architecture, and automation frameworks.
• Hands-on experience in data testing, ETL/ELT pipelines, and big data platforms.
• Understanding of AI/ML lifecycle including training, validation, deployment, and monitoring.
• Experience in testing AI/ML models (accuracy, drift, fairness, explainability).
• Proficiency in Python, PyTest, Robot Framework, or similar automation tools.
• Familiarity with data quality tools (e.g., Great Expectations, Soda, Deequ).
• Experience with AWS cloud services (S3, Glue, Lambda, SageMaker, Athena, Redshift, Step Functions).
• Strong problem-solving and analytical thinking.
• Excellent communication and stakeholder management skills.

3 Must Haves:

• Python
• Selenium
• AWS
• AI/ML