Senior AI QA Engineer — Model Validation & Governance

Envestnet; Springfield (IL); Hybrid; USD 152,000 - 190,000; Full time

Benefits offered by this job

Medical insurance

401k match

Parental leave

Education reimbursement

Mental health support

Job summary

Envestnet’s Quality Assurance Engineering team ensures AI-enabled solutions are accurate, reliable, secure, and compliant while aligning with business expectations. You will collaborate across engineering, data science, product, cybersecurity, legal, and risk teams to validate AI-driven products and processes.

You will design test plans for model accuracy and governance, build automated frameworks, and mentor analysts to uphold high testing standards in a hybrid environment.

Qualifications

• Experience validating AI/ML models, Generative AI apps, or data science solutions.
• Knowledge of AI concepts, machine learning fundamentals, and risk considerations.
• Experience with automated testing frameworks and API testing.

Responsibilities

• Lead testing efforts for moderately complex AI products, features and platform improvements.
• Design advanced test plans covering model accuracy, bias, explainability, and resilience.
• Develop automated testing frameworks and monitoring for AI systems.
• Analyze defects, model drift, and production quality issues.
• Define acceptance criteria and quality standards with cross-functional teams.
• Mentor junior analysts and review testing deliverables.

Skills

AI concepts

Quality assurance

Cross-functional collaboration

Automation testing

Model validation

Data quality

Regulatory governance

Communication skills

Tools

API testing tools

Model evaluation tooling

Job description

Envestnet’s Quality Assurance Engineering team ensures AI-enabled solutions are accurate, reliable, secure, and compliant while aligning with business expectations. You will collaborate across engineering, data science, product, cybersecurity, legal, and risk teams to validate AI-driven products and processes.

You will design test plans for model accuracy and governance, build automated frameworks, and mentor analysts to uphold high testing standards in a hybrid environment.