Key skills
AWSAzureCloudGoogle Cloud PlatformPythonSeleniumAIMLAgenticStatistical AnalysisPlaywrightPytestGCPGoogle CloudGitHubAgileLeadershipCommunicationCollaboration
About this role
Role Overview
- Define and drive end-to-end test strategy and governance for AI systems
- Lead and mentor QE teams delivering AI testing engagements
- Oversee data validation, model evaluation, anomaly detection, and statistical analysis
- Ensure AI systems meet functional, performance, ethical, and responsible AI requirements
- Establish metrics and KPIs to measure AI system effectiveness and quality
- Manage stakeholder communication across clients and internal teams
- Plan and forecast resource requirements for AI testing engagements
- Drive adoption of best practices, tools, and frameworks across AI testing delivery
- Identify risks in AI models and define mitigation strategies
- Prepare and present testing reports, risks, and progress updates to stakeholders
- Maintain documentation of testing processes, results, and learnings
Requirements
- Strong understanding of AI/ML concepts, LLMs, and Agentic AI systems
- Ability to define validation strategies for AI models and systems
- Experience managing global stakeholders and client interactions
- Expertise in test automation tools (e.g., Selenium, Playwright, PyTest)
- Proficiency in Python programming
- Exposure to GitHub Copilot or similar AI-assisted development tools
- Strong understanding of cloud platforms (Azure, AWS, GCP)
- Experience working in Agile environments
- Strong analytical, problem-solving, and decision-making skills
- Excellent communication, leadership, and collaboration skills
- Ability to operate in fast-paced, dynamic environments
Tech Stack
- AWS
- Azure
- Cloud
- Google Cloud Platform
- Python
- Selenium
Benefits
- Health and wellness packages
- Learning opportunities