Senior AI Test Engineer

TestPros delivers innovative independent IT assessment solutions to critical challenges facing the nation and the world. We support the U.S. Federal/State/Local Government and Commercial clients within the continental USA. TestPros is dedicated to making lives better, safer and more secure.

TestPros is seeking a Senior Artificial Intelligence (AI) System Test Engineer with an analytical, customer-focused mindset and experience with the OWASP AI Testing Guide and other guidelines from NIST, ISO, and IEEE.

Start: Future projects in late 2026 or 2027 (not an immediate job opening)

Type: Part-time consulting

Overview
Focus: Software test end evaluation

Regulatory Basis: OWASP AI Testing Guide

Location: Remote, with occasional travel to customer sites or TestPros labs in Sterling, VA

This role evaluates AI systems and software for alignment with the intended functions and features, plus additional assessment focused on AI-specific validation, including model robustness, data integrity, adversarial defense, performance, usability, reliability, security, maintainability, safety, and other aspects of overall quality.
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Key Responsibilities:
Develop and execute test plans and evaluate software for compliance with the OWASP AI Testing Guide and other guidance, create defect and remediation records, capture test evidence and document defects with clear reproduction steps and severity ratings, report results to senior management and stakeholders.
Required Skills.

- Bachelor's degree in computer science, engineering or a related field.

- 10+ years of experience in Software/System Testing and Quality Engineering (QE), including enterprise-scale transformation programs.

- 4+ years hands-on experience defining the testing strategy for large scale programs and ensuring requirements traceability throughout the system development lifecycle. Experience should include leading the testing efforts, including experience with all phases of testing: system integration, user acceptance, and performance testing.

- A deep understanding of testing planning and associated delivery challenges.

- A strong understanding of the various approaches used in testing techniques - white-box, black-box, load testing, coverage testing and regression testing.

- Proven experience in defining and executing QE transformation strategy.

- Hands-on expertise in Agentic AI / GenAI frameworks (e.g., LangChain, AutoGen, CrewAI, Cursor, etc.).

- Experience working in Cloud, Web and Mobile Testing platforms - Saucelabs, Browerstack are preferred.

- Hands-on experience with machine learning models.

- Experience in Python NLTK or similar natural language processing technology.

- Practical experience implementing AI-driven QE solutions such as:

- Autonomous test generation

- Self-healing automation

- Defect prediction and intelligent triaging

- Expertise in test automation tools (Selenium, Playwright, Cypress, etc.).

- Strong experience with CI/CD pipelines and DevOps integration (GitHub).

- Solid understanding of API, microservices, and cloud-native architectures.

- Experience evaluating or testing Artificial Intelligence (AI) Large Language Model (LLM)-based application features (e.g., chatbots, copilots, RAG-based systems), including prompt-response validation and hallucination/edge-case testing.

- Exposure to AI-assisted defect triage or root-cause analysis tools that reduce manual investigation time.

- Experience with cloud platforms (AWS, Azure, GCP) in QE/AI context.

- Exposure to self-healing test automation frameworks (AI-driven locator repair, visual AI testing).

- Understanding of responsible AI/testing governance principles (bias detection, explainability, model validation) as applied to QE.

- Experience contributing to or influencing AI-adoption roadmaps within a testing/QE organization.

- Experience implementing testing best practices specific to the test planning and execution processes and gaining buy-in for changes from executiv