QA Lead – AI/ML Systems

India·Punelead

OtherQa Lead

0 views0 saves0 applied

Apply Now

Quick Summary

Overview

Company OverviewAt Codvo, software and people transformations go hand-in-hand. We are a global empathy-led technology services company. Product innovation and mature software engineering are part of our core DNA.

Key Responsibilities

Own and drive QA strategy for AI systems across the model, data, and product lifecycle. Lead AI model validation efforts, covering LLM/RAG testing, bias analysis, and performance evaluation.

Requirements Summary

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Biomedical Engineering, or related field. 8–12 years of total QA experience, with 2–3 years directly in AI/ML or GenAI QA.

Technical Tools

awsazurepython

Company Overview
At Codvo, software and people transformations go hand-in-hand. We are a global empathy-led technology services company. Product innovation and mature software engineering are part of our core DNA. Respect, Fairness, Growth, Agility, and Inclusiveness are the core values that we aspire to live by each day.

We continue to expand our digital strategy, design, architecture, and product management capabilities to offer expertise, outside-the-box thinking, and measurable results.

About the Role

We are looking for an experienced QA Lead – AI Systems to lead the validation and quality assurance of AI-powered products, including LLM/RAG systems, Software as a Medical Device (SaMD), and other AI-driven digital solutions.

This is a key leadership role responsible for establishing end-to-end QA frameworks, validation strategies, and compliance processes for AI/ML models across development and deployment pipelines. The ideal candidate will bridge data science, software engineering, and regulatory QA to ensure AI systems meet performance, safety, and compliance standards.

Key Responsibilities

Own and drive QA strategy for AI systems across the model, data, and product lifecycle.
Lead AI model validation efforts, covering LLM/RAG testing, bias analysis, and performance evaluation.
Define and implement AI Evaluation Metrics (accuracy, fairness, drift, explainability) aligned with business and regulatory expectations.
Establish frameworks for Explainability Testing (SHAP, LIME, XAI) and ensure interpretability of AI outcomes.
Collaborate with Data Science and MLOps teams to validate models within cloud environments (Azure ML, AWS Sagemaker, Vertex AI).
Drive verification and validation (V&V) for AI models and applications under FDA and SaMD compliance frameworks.
Ensure test traceability, documentation, and audit readiness in line with ISO 13485, IEC 62304, and ISO 14971.
Develop Python-based automation for AI testing, data validation, and model evaluation pipelines.
Provide technical leadership to QA teams, ensuring alignment with AI/ML development best practices.
Collaborate with cross-functional teams (Product, Data, Regulatory, Engineering) to identify risks, gaps, and opportunities for test optimization.
Present validation findings, risks, and recommendations to senior stakeholders and regulatory reviewers.

Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Biomedical Engineering, or related field.
8–12 years of total QA experience, with 2–3 years directly in AI/ML or GenAI QA.
Proven experience in AI Model Validation, LLM/RAG Testing, and AI Evaluation Metrics.
Strong knowledge of MLOps concepts and cloud platforms (Azure ML, AWS Sagemaker, Vertex AI).
Understanding of FDA AI/ML Compliance, SaMD testing, and regulated software QA.
Hands-on expertise in Python automation and testing AI/ML pipelines.
Excellent documentation and communication skills with ability to produce traceable validation artifacts