Job Summary The QA/QC Construction Engineer is responsible for ensuring that construction works are executed according to project specifications, drawings, codes, standards, and client requirements. The role involves implementing quality assurance and quality control procedures, conducting inspections, managing documentation, and coordinating with project teams to achieve quality objectives.
We are seeking an experienced Automation Testing + AI Model Assurance Engineer to validate and assure the quality, reliability, performance, and governance of AI-powered applications and conversational systems. The ideal candidate should have strong expertise in test automation frameworks, API testing, AI model validation, prompt testing, and quality assurance practices across Generative AI and Machine Learning solutions.
The role involves designing automation frameworks, validating AI model behavior, testing conversational AI experiences, identifying model risks, and collaborating with cross-functional teams to ensure high-quality AI product releases.
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Design, build and scale testing capabilities using AI agents – using GitHub Copilot Agent Mode on the GitHub Enterprise platform and the Microsoft AI Foundry stack – to automate testing tasks such as test case generation, test data creation, defect triage, and regression analysis.
Develop and run AI evaluation (AI eval) frameworks and metrics to measure the accuracy, reliability, and performance of AI agents and Gen-AI-assisted testing workflows and iterate on prompts and agent design based on eval results.
Write efficient test automation code using coding standards and best practices.
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Quality Assurance Reviews: Conduct regular quality audits on customer interactions to ensure compliance with SOPs, communication standards, and solution accuracy. Provide structured coaching using established frameworks to drive agent performance improvement.
Quality Framework & Governance: Maintain and enhance QA frameworks including scorecards, coaching approaches, and audit standards to ensure consistency, fairness, and continuous improvement across teams.
Reporting & Insights: Prepare concise, data-driven reports to highlight performance trends, gaps, and risks. Communicate actionable recommendations to stakeholders and track the effectiveness of implemented actions.
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