Lead AI Quality Assurance Engineer

Quality Assurance Engineering Team Member

The primary work location for this role is Berwyn, Raleigh, Boston, Chicago, or Seattle with a hybrid work model.

Join the Quality Assurance Engineering team, which plays a critical role in ensuring the reliability, security, and effectiveness of Envestnet's technology solutions, with a growing focus on AI-enabled products and platforms. Working at the intersection of engineering, data science, product, cybersecurity, and business operations, the team develops and executes innovative testing and validation strategies that help deliver trusted experiences for clients and internal stakeholders alike.

By championing quality, governance, automation, and continuous improvement, the team helps accelerate the adoption of emerging technologies while ensuring solutions are scalable, compliant, and built to meet the highest standards of performance and customer confidence.

Ensures that artificial intelligence solutions are accurate, reliable, secure, compliant and aligned with business and client expectations. Combines traditional QA practices with AI/ML validation techniques to test data integrity, model performance, automation workflows and user outcomes. Works with engineering, data science, product management, cybersecurity, legal and risk teams to validate AI-enabled products and operational processes. Continuously improves testing frameworks, monitoring methodologies, governance standards and automation capabilities to support scalable and trustworthy AI adoption.

• Leads testing efforts for moderately complex AI products, features and platform enhancements.
• Designs advanced test plans covering model accuracy, bias detection, explainability and operational resilience.
• Develops automated testing frameworks and monitoring approaches for AI systems.
• Performs detailed analysis of defects, model drift and production quality issues.
• Partners with cross-functional stakeholders to define acceptance criteria and quality standards.
• Mentors junior analysts and reviews testing deliverables for quality and consistency.
• Supports implementation of enterprise AI governance and risk management controls.
• Recommends improvements to testing methodologies, tooling and operational processes.
• Facilitates quality reviews, stakeholder workshops, model validation discussions, and testing strategy sessions.
• Identifies operational, technical, compliance, and model-related risks and recommends mitigation strategies.
• Leads validation activities for AI models, data pipelines, automation workflows, user-facing AI capabilities, vendors, tools, and third-party technologies.
• Evaluates quality, reliability, security, governance, and compliance considerations associated with AI products and services.

Candidates should demonstrate the relevant experience, skills, and capabilities needed to successfully perform in the role. Relevant experience may be gained through current responsibilities, prior roles, project work, leadership opportunities, or other comparable experiences. Ability to evaluate complex problems, identify root causes, assess alternatives, and implement practical, scalable, data-driven solutions. Demonstrated ability to establish and maintain productive relationships across business, technology, product, engineering, data science, and risk organizations.

Knowledge of process improvement techniques, operational workflows, dependency management, quality optimization, and governance practices. Ability to communicate technical and non-technical concepts clearly to diverse audiences, including leadership stakeholders. Experience coordinating cross-functional initiatives, managing dependencies, tracking progress, and delivering measurable outcomes. Strong understanding of AI concepts, machine learning fundamentals, AI system capabilities, limitations, risks, and practical applications, with experience validating AI/ML models, Generative AI applications, LLM-enabled systems, or data science solutions.

Experience with automated testing frameworks, API testing, model evaluation, prompt testing, hallucination testing, data quality validation, AI governance controls, and regulatory, security, privacy, or responsible AI requirements.

Help shape the future of Wealth Tech. At Envestnet you'll gain hands-on experience and collaborate with some of the industry's brightest minds to deliver meaningful, innovative solutions that make a real difference. We value flexibility in how and where work gets done, and we recognize strong performance with meaningful rewards—because your contributions should drive both business success and your own personal growth.

If you're looking for a place where your work has impact, your development is supported, and your contributions are truly valued, Envestnet is where you can build your future.

This role offers a base salary range of $152,300 to $190,400. The range listed represents a good-faith estimate of base salary compensation for this position and does not include incentive compensation,…