Automation Engineer (AIML-Driven Automation)

Senior Automation Engineer (AI/ML-Driven Automation)

Experience: 8 12 Years

Role Summary

The Senior Automation Engineer designs and scales intelligent AI-assisted automation solutions across applications platforms and data systems. The role focuses on advanced test automation predictive quality and validation of AI/ML systems driving measurable reductions in cycle time and production defects.

Key Responsibilities

• Design and own end-to-end automation architecture covering UI API backend data and cloud layers.
• Implement AI/ML-enabled automation such as self-healing tests predictive test selection and flakiness detection.
• Lead automation integration into CI/CD pipelines with quality gates and intelligent feedback loops.
• Develop robust test data strategies using synthetic data data modeling and ML-driven generation.
• Validate AI/ML models and pipelines for data quality bias performance drift and reliability.
• Enable quality for microservices event-driven containerized and distributed systems.
• Drive shift-left and shift-right testing leveraging observability and production insights.
• Perform root cause analysis using logs traces metrics and AI-based diagnostic tools.
• Review automation code enforce standards and mentor engineers.
• Partner with Product Platform Data Science and DevOps teams to embed quality by design.

Mandatory Experience Requirements

• 8 12 years of overall experience in Automation Engineering / Quality Engineering.
• 5 years of hands-on experience building and maintaining large-scale automation frameworks.
• 3 years working in CI/CD-driven Agile or DevOps environments.
• Proven experience testing cloud-native microservices-based systems.
• Demonstrated experience applying AI/ML concepts or tools within automation or quality workflows.

Mandatory Technical Skills

Automation & Programming (Must-Have)

• Strong hands-on expertise in Selenium / Playwright / Cypress / Appium / REST Assured.
• Proficient in Java or Python (mandatory); ability to design reusable maintainable frameworks.
• Deep understanding of API Contract Integration and End-to-End Automation.

AI/ML & Intelligent Automation (Must-Have)

• Experience implementing AI-assisted automation (self-healing locators smart test execution defect prediction).
• Solid understanding of ML fundamentals:
  • Supervised vs Unsupervised learning
  • Model evaluation metrics
  • Data drift and model degradation
• Exposure to GenAI/LLMs for test generation automation acceleration or analysis.

DevOps Cloud & Data (Must-Have)

• Strong experience with CI/CD tools (Azure DevOps GitHub Actions Jenkins etc.).
• Hands-on knowledge of Docker and Kubernetes.
• Working experience with cloud platforms (Azure/AWS/GCP at least one mandatory).
• Ability to analyze logs metrics and traces for quality and reliability insights.

Nice to Have (Non-Mandatory)

• Experience with MLOps pipelines and automated model testing.
• Exposure to data platforms (Spark Databricks Airflow).
• Security and performance testing automation experience.
• Relevant certifications in Automation Cloud or AI/ML.

Behavioral & Leadership Expectations

• Strong system-level thinking with an outcome-driven mindset.
• Ability to influence quality strategy beyond assigned modules.
• Effective communicator with engineering product and data stakeholders.
• Mentors team members and drives automation maturity.

Success Metrics

• Reduction in test execution time and flaky tests.
• Improved defect prevention and predictive quality insights.
• Increased adoption of AI-driven automation practices.
• Higher release confidence and production stability.