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# SDET - AI/ML Testing

- **Company:** Vision Square
- **Location:** Alpharetta, GA, United States
- **Salary:** $83,200.0 - $87,360.0
- **Contract:** Contract
- **Skills:** AI Evaluation, Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Application Performance Management, Automation of Tests, Microsoft Azure, Software Bug Management, Code Review, Computer Programming, Databases, Continuous Integration, Data Validation, DevOps, Distributed Systems, Github, Junit, Python (Programming Language), Machine Learning, E2e Testing, Software Safety, Selenium, Software Engineering, Test Data, Strategies of Testing, TypeScript, Circleci, Google Cloud, Retrieval-Augmented Generation, Appium, Prompt Engineering, Hallucination Detection, Model Validation, Cypress (Programming Language), Generative AI, Backend, Pytest, Gitlab-ci, Playwright, Machine Learning Operations, Restful APIs, Data Pipelines, SDET, Jenkins, Microservices
- **Published:** October 28, 2026
- **Apply:** https://www.dice.com/job-detail/a2b07fe3-8016-4a86-b16b-c2e36d141e19

## About the Role

* Experience in SDET, software development, test automation, or quality engineering.
 * Strong programming skills in Python, Java, JavaScript, or TypeScript.
 * Proven experience designing and maintaining automation frameworks.
 * Strong understanding of software testing methodologies, test strategy, and defect management.
 * Experience testing RESTful APIs, microservices, databases, and distributed systems.
 * Hands-on experience with Selenium, Playwright, Cypress, Appium, REST Assured, PyTest, JUnit, or equivalent tools.
 * Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, Azure DevOps, or CircleCI.
 * Exposure to cloud platforms such as AWS, Azure, or Google Cloud.
 * Practical experience testing AI/ML systems, models, data pipelines, or AI-powered applications.
 * Understanding of machine learning concepts, model evaluation, data validation, and statistical testing.
 * Strong analytical, troubleshooting, communication, and problem-solving skills.

Preferred Qualifications

 * Experience testing generative AI and LLM-based applications.
 * Knowledge of hallucination detection, prompt evaluation, bias testing, and AI safety.
 * Experience validating RAG systems, model outputs, and prompt engineering workflows.
 * Familiarity with AI evaluation benchmarks, test datasets, and automated quality monitoring.

## Description

We are seeking an experienced Software Development Engineer in Test (SDET) with strong software engineering, test automation, and AI/ML quality assurance expertise. The ideal candidate will design and maintain scalable automation frameworks and develop testing strategies for traditional software applications as well as AI-powered and generative AI systems.

You will collaborate with software engineers, data scientists, product managers, and DevOps teams to ensure the functionality, performance, reliability, security, and quality of applications throughout the software development lifecycle., * Design, develop, and maintain scalable automation frameworks for web, mobile, API, and backend applications.

 * Develop comprehensive testing strategies for AI/ML-powered products and services.
 * Automate functional, regression, integration, API, and end-to-end testing.
 * Validate application performance, scalability, reliability, and security.
 * Test data quality, data pipelines, model accuracy, consistency, and edge cases.
 * Evaluate generative AI applications for response quality, hallucinations, factual accuracy, toxicity, bias, and harmful content.
 * Test prompt injection, jailbreak resistance, response consistency, and model or prompt regressions.
 * Validate Retrieval-Augmented Generation (RAG) workflows and AI-driven application behavior.
 * Develop tools for test data generation, model evaluation, monitoring, and reporting.
 * Integrate automated testing into CI/CD pipelines and establish quality gates.
 * Perform root-cause analysis, troubleshoot complex defects, and communicate risks and recommendations.
 * Establish quality metrics, dashboards, and reports for software and AI/ML systems.
 * Collaborate with engineering and data science teams to identify defects early and improve product quality.
 * Participate in test planning, code reviews, architecture discussions, and release readiness assessments.
 * Mentor team members and promote automation and quality engineering best practices.