AI Infusion QE Leader

Overview

On Site
$160,000 - $170,000
Full Time

Skills

Artificial Intelligence
Automated Testing
Data Cleansing
Data Quality
Defect Management
Quality Assurance
System Testing
Integration Testing
Bug Tracking

Job Details

AI Infusion QE Leader
Location:: Chicago, IL Onsite

As discussed below are the details.

An AI Infusion QE Leader is responsible for integrating and ensuring the quality of AI models within a company's products or services. This role involves leading a team of quality assurance professionals to test and validate AI-powered systems, ensuring they meet performance, reliability, and security standards.

Key Responsibilities: This role must be able to drive AI infusion across our QE footprint. Cannot be an AI generalist and must be able to drive across the Insurance value chain.

Here's a more detailed breakdown of the responsibilities:

  1. Leading the AI Infusion QE Team:
  • Team Leadership:

Lead, mentor, and guide a team of quality engineers specializing in AI integration. This includes setting goals, providing feedback, and promoting a collaborative work environment.

  • Strategy & Planning:

Develop and execute quality assurance strategies for AI-infused products, including test plans, scenarios, and automation frameworks.

  • Resource Management:

Ensure the team has the necessary resources and tools to effectively test AI-powered systems.

  1. AI-Specific QA Tasks:
  • Model Evaluation:

Assess the performance of AI models, including accuracy, fairness, bias, and explainability. This may involve using various metrics and tools to evaluate model output.

  • AI-Driven System Testing:

Develop and execute comprehensive testing procedures for AI-powered systems, including integration testing, edge case scenarios, and adversarial testing.

  • Data Quality Assurance:

Ensure the quality and integrity of data used to train and deploy AI models, including data cleaning, validation, and anomaly detection.

  • Continuous Integration and Continuous Delivery (CI/CD) Integration:

Work with development teams to integrate QA processes into the CI/CD pipeline for AI models.

  • Defect Management:

Prioritize and track defects related to AI-infused systems, ensuring timely resolution.

  1. Collaboration and Communication:
  • Cross-Functional Collaboration:

Work closely with AI developers, data scientists, product managers, and other stakeholders to ensure seamless integration of AI into products.

  • Communication & Reporting:

Communicate QA status, issues, and findings to relevant stakeholders in a clear and concise manner.

  • Knowledge Sharing:

Stay up-to-date with the latest advancements in AI and QA, sharing this knowledge with the team.

  1. Tools and Technologies:
  • QA Tools:

Utilize various QA tools, including test automation frameworks, bug tracking systems, and performance monitoring tools.

  • AI-Specific Tools:

Leverage AI-specific tools and libraries for model evaluation, bias detection, and adversarial testing.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

About Nexo Global Inc.