AI Quality Assurance Lead: Trusted, Scalable AI

Envestnet; Boston (MA); Hybrid; USD 152,000 - 190,000; Full time

Benefits offered by this job

Medical insurance

PTO

401k match

Parental leave

Education reimbursement

Disability coverage

Mental health support

Job summary

Envestnet is seeking a Quality Assurance Engineer to ensure AI solutions are accurate, secure, and compliant. You will combine traditional QA with AI/ML validation to test data integrity, model performance and automation workflows.

You will work with engineering, data science, product management, cybersecurity, and risk teams to validate AI-enabled products and processes. You will lead testing for moderately complex AI features, design tests for bias detection and explainability, and develop

Qualifications

• Experience validating AI/ML models, Generative AI apps or data science solutions.
• Ability to design test plans for model accuracy, bias and explainability.
• Experience with automated testing frameworks and API testing.

Responsibilities

• Lead testing efforts for moderately complex AI products and platforms.
• Design advanced test plans covering model accuracy, bias and resilience.
• Develop automated testing frameworks and monitoring approaches for AI systems.
• Collaborate with engineering, data science, product, and risk teams to validate AI-enabled products.
• Mentor junior analysts and review testing deliverables for quality.

Skills

AI validation

Model evaluation

Automated testing

Cross-functional collaboration

Tools

API testing

ML testing frameworks

Job description

Envestnet is seeking a Quality Assurance Engineer to ensure AI solutions are accurate, secure, and compliant. You will combine traditional QA with AI/ML validation to test data integrity, model performance and automation workflows.

You will work with engineering, data science, product management, cybersecurity, and risk teams to validate AI-enabled products and processes. You will lead testing for moderately complex AI features, design tests for bias detection and explainability, and develop