OT AI Test and Assurance Engineer

Strategic Staffing Solutions; Argentina; Remote; ARS 138,361,000 - 230,602,000; Full time

Benefits offered by this job

100% remote

Global enterprise projects

Job summary

Strategic Staffing Solutions is seeking an experienced OT Artificial Intelligence Test and Assurance Engineer to independently verify safety, security, reliability, and fit-for-use of AI-enabled solutions in industrial operations.

The role focuses on AI testing, verification and validation, risk-based assurance, and quality engineering across data, models, applications, integrations, edge platforms, and OT workflows. Remote, highly technical, and collaborative with OT cybersecurity teams.

Qualifications

• 5+ years of experience in Software Engineering, Systems Engineering, Automation, or Quality Engineering with production verification/validation responsibilities.
• Experience developing risk-based test strategies, acceptance criteria, test cases, requirements traceability, and release evidence.
• Experience testing ML/CV/analytics or data-driven systems using performance and error metrics.
• Experience evaluating datasets for quality, representativeness, data leakage, imbalance, labeling accuracy, and version control.
• Strong hands-on experience with Python, automated testing frameworks, APIs, data validation, source control, and CI/CD pipelines.
• Experience with system, integration, performance, resilience, cybersecurity, and user-acceptance testing.
• Knowledge of AI limitations, model uncertainty, drift, monitoring, and human oversight.
• Understanding of OT cybersecurity and industrial environments, including network segmentation and constrained connectivity.

Responsibilities

• Develop and execute risk-based testing, verification, validation, and assurance strategies for AI-enabled solutions.
• Translate requirements into measurable test cases and acceptance criteria.
• Evaluate training, validation, and test datasets for quality and labeling accuracy.
• Test AI/ML models using performance metrics (accuracy, precision, recall, false positives/negatives).
• Design and execute scenario-based, boundary, negative, fault-injection, and adversarial tests for ML, CV, Generative AI, and agentic systems.
• Perform end-to-end system, integration, performance, resilience, and user-acceptance testing across applications, APIs, edge devices, and OT environments.
• Verify behavior under abnormal, degraded, and recovery conditions (fallback, fail-safe, rollback, manual override).
• Assess cybersecurity controls, access management, network segmentation, logging, and auditability with OT security teams.
• Automate regression, integration, and performance testing using Python and testing frameworks.
• Document results, defects, residual risks, and release recommendations.
• Define post-deployment monitoring to identify model degradation and operational risks.

Skills

Python

Automated testing frameworks

APIs

Data validation

CI/CD pipelines

Software testing

System testing

Tools

Git

GitHub Actions

Azure DevOps

Job description

We are looking for an experienced OT Artificial Intelligence Test and Assurance Engineer to independently verify that AI-enabled solutions are safe, secure, reliable, and fit for use in industrial operations.

This is a hands‑on role focused on AI testing, verification and validation, risk-based assurance, and quality engineering. The ideal candidate will evaluate the complete AI solution lifecycle, including data, models, applications, integrations, edge platforms, and operational workflows, ensuring solutions meet technical, security, and operational requirements before deployment and throughout production.

Key Responsibilities

• Develop and execute risk-based testing, verification, validation, and assurance strategies for AI-enabled solutions.
• Translate operational, safety, cybersecurity, and business requirements into measurable test cases and acceptance criteria.
• Evaluate training, validation, and test datasets for quality, accuracy, representativeness, data leakage, and labeling consistency.
• Test AI and Machine Learning models using appropriate performance metrics, including accuracy, precision, recall, false positives, and false negatives.
• Design and execute scenario-based, boundary, negative, fault‑injection, and adversarial tests for Machine Learning, Computer Vision, Generative AI, and agentic systems.
• Perform end‑to‑end system, integration, performance, resilience, and user‑acceptance testing across applications, APIs, edge devices, and OT environments.
• Verify system behavior under abnormal, degraded, and recovery conditions, including fallback, fail‑safe, rollback, and manual override mechanisms.
• Assess cybersecurity controls, access management, network segmentation, logging, and system auditability in collaboration with OT Cybersecurity teams.
• Automate regression, integration, and performance testing using Python and appropriate testing frameworks.
• Document test results, defects, residual risks, and release recommendations, ensuring corrective actions are properly addressed.
• Define post‑deployment monitoring and assurance activities to identify model degradation, performance drift, and potential operational risks.

Required Qualifications

• 5+ years of experience in Software Engineering, Systems Engineering, Automation, or Quality Engineering, including production verification and validation responsibilities.
• Demonstrated experience developing risk‑based test strategies, acceptance criteria, test cases, requirements traceability, and release evidence.
• Experience testing Machine Learning, Computer Vision, analytics, or other data‑driven systems using appropriate performance and error metrics.
• Experience evaluating datasets for quality, representativeness, data leakage, imbalance, labeling accuracy, and version control.
• Strong hands‑on experience with Python, automated testing frameworks, APIs, data validation, source control, and CI/CD pipelines.
• Experience with system, integration, performance, resilience, cybersecurity, and user‑acceptance testing.
• Understanding of AI limitations, model uncertainty, performance drift, monitoring, and human oversight.
• Understanding of OT cybersecurity and industrial environments, including network segmentation, constrained connectivity, high availability, and controlled change management.
• Ability to evaluate system behavior under normal, abnormal, degraded, and recovery conditions.
• Strong analytical, problem‑solving, documentation, and communication skills.
• Ability to independently assess technical risks, challenge assumptions, and make evidence‑based release recommendations.

Nice to Have

• Experience testing Generative AI, RAG, agentic systems, or multimodal AI solutions.
• Experience with Computer Vision testing under varying lighting, weather, motion, occlusion, and equipment conditions.
• Knowledge of adversarial testing, red teaming, model robustness, explainability, and responsible AI.
• Familiarity with safety and assurance standards such as IEC 61508, IEC 61511, IEC 62443, or the NIST AI Risk Management Framework.
• Experience with Azure Machine Learning, Microsoft Foundry, Azure DevOps, or GitHub Actions.
• Experience with simulation, digital twins, hardware‑in‑the‑loop, or software‑in‑the‑loop testing.
• Previous experience in the Oil & Gas industry or other industrial environments.

What We Offer

• 100% remote.
• Opportunity to work on global enterprise projects with an international team.