Senior Artificial Intelligence Test Engineer

Overview

Remote
Up to $60
Contract - W2
Contract - 4 Month(s)

Skills

"quality Assurance"
pytest
"GPT"
SQL
"artificial intelligence"
"API Testing"
"backend testing"

Job Details

Senior Artificial Intelligence Test Engineer
Location: Hybrid of 3 days/month onsite during the 2 nd full week of each month in either Denver, CO/Brentwood, TN/Malvern, PA or 100% remote with travel 2-3 times/year (if remote)
Duration - 3 6-month Contract to Hire Opportunity
Working Hours Mon-Fri, from 8AM 5PM EST

This is an exciting opportunity to join a new team that will be supporting the testing efforts for AI products within an industry leading healthcare organization. This team will be solving exciting use cases using AI models. This QA Engineer will be getting in at the ground level and there will be a lot of growth opportunities. This Senior Test Engineer will be responsible for leading test automation efforts and leveraging their knowledge in backend systems and AI-driven testing methodologies. They will work closely with cross-functional teams, including developers, data scientists, and product managers, to build scalable and intelligent testing frameworks. Their expertise will be crucial in developing generative AI models for test case generation, predictive test selection, and failure analysis, all while ensuring the reliability, performance, and security of our backend systems. They will also be responsible for leading Scrum Meetings from the QA side.

The ideal candidate will be very familiar with Python as well as skilled in writing complex SQL Queries, and validating AI models using Python.

Responsibilities will include the following:

  • Test Automation & AI Integration:
    • Lead the development and maintenance of test automation frameworks using Python and AI-driven technologies.
    • Design and implement generative AI-based solutions to automate test case generation, smart test selection, and failure diagnosis.
    • Develop machine learning models to predict test failures, prioritize tests, and optimize test coverage.
  • Backend System Testing:
    • Perform backend testing for APIs, databases, and other backend services, ensuring data integrity, security, and performance.
    • Collaborate with backend engineers to write effective test plans and ensure that APIs and systems meet product requirements.
    • Implement performance testing and load testing for backend systems, utilizing AI tools to simulate real-world conditions.
  • Data Science for Test Optimization:
    • Apply statistical and machine learning techniques to analyze historical test data and improve testing efficiency.
    • Leverage data analytics to identify patterns, predict defect trends, and propose actionable insights to improve software quality.
    • Utilize advanced data visualization tools to communicate test results and quality metrics to stakeholders.
  • Test Result Analysis & Reporting:
    • Use AI and natural language processing (NLP) techniques to analyze logs, error messages, and test results.
    • Build predictive models to classify test failures and suggest potential fixes based on historical data and known defect patterns.
    • Automate test result analysis, generating reports with actionable insights and providing root cause analysis for complex issues.
  • AI-Driven Test Data Generation:
    • Use generative AI models to create synthetic, realistic test data for complex backend and API testing scenarios.
    • Ensure AI-generated test data covers edge cases, rare conditions, and potential failure points that traditional testing might miss.
  • Collaboration & Leadership:
    • Collaborate closely with development, data science, and product teams to ensure comprehensive test coverage and integration of AI-based testing techniques.
    • Mentor junior engineers, providing guidance on test automation, AI-based testing, and data-driven quality assurance practices.
    • Drive the adoption of AI-powered testing tools and frameworks within the team and across the organization.

Required Skills and Experience:

  • Experience:
    • 8 + years of experience in software testing, with at least 5 years of experience in test automation and backend testing.
    • Strong background in Python, with hands-on experience in writing automation scripts and developing test frameworks.
    • Solid experience with backend technologies (e.g., REST APIs, databases, microservices).
    • Familiarity with AI/ML frameworks like TensorFlow, PyTorch, or Scikit-learn, with practical experience in applying AI to testing.
    • Proven experience using generative AI models (e.g., GPT, T5) for test case generation, failure analysis, or data augmentation.
    • Well-versed in working with SQL and writing complex SQL Queries
    • Thorough understanding of the QA process
    • Strong background in automating QA testing efforts
    • Experience working within an Agile/Scrum environment
  • Technical Skills:
    • Proficiency in test automation tools such as pytest or other tools
    • Knowledge of API testing and performance testing tools like Postman, Swagger, and Gatling.
    • Familiarity with CI/CD pipeline integration (Jenkins, GitLab CI, CircleCI) and version control systems (Git).
    • Strong understanding of databases (SQL, NoSQL) and experience with backend testing for data integrity and performance.
  • Data Science & Analytics:
    • Strong statistical analysis skills, with the ability to apply data science methods to improve testing efficiency.
    • Ability to derive actionable insights from large datasets and communicate findings to both technical and non-technical stakeholders.
  • Soft Skills:
    • Excellent problem-solving skills with a keen eye for detail.
    • Strong communication skills, with the ability to collaborate effectively with cross-functional teams.
    • Leadership qualities and the ability to mentor and guide junior engineers.
    • Passion for continuous learning and staying up to date with the latest trends in testing, AI, and backend technologies.
    • Exemplifies teamwork and serves as role model, while also successfully facilitating collaboration across multiple functions, departments, and levels.
    • Unquestionable ethics & integrity is pertinent.

Preferred Qualifications:

  • Master's Degree in Computer Science, Data Science, or related fields.
  • Experience with cloud-based backend technologies (AWS, Azure, Google Cloud Platform) and cloud-native testing practices.
  • Healthcare background preferred but not mandatory.
  • Familiarity with advanced machine learning techniques and NLP for automated defect analysis and root cause identification.
  • Prior experience in building or contributing to AI-driven test frameworks and tools.
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