AI Quality Engineer

AI Quality Engineer

This is a HYBRID position requiring 2 in-office days at local client office per week. Travel costs are not reimbursable. Duration: 6+ Months Only W2.

We are seeking an AI Quality Engineer to join an innovative and high-impact team building AI capabilities within enterprise systems for a leading wealth management client. In this role, you will define, execute, and continuously improve quality engineering practices for AI-powered applications, including LLM-based assistants, retrieval solutions, and intelligent workflows. You will help ensure these solutions are reliable, accurate, secure, and fit for enterprise use by building robust testing strategies across model behavior, system integrations, user experience, and operational performance. This is an opportunity to shape the next generation of enterprise AI in a highly visible environment, where innovation, rigor, and business value all matter. The ideal candidate brings a quality-first mindset, strong testing discipline, and practical experience validating complex systems in regulated environments.

Key Responsibilities:

• Design and execute test strategies for AI applications, including functional, integration, regression, usability, and non-functional testing
• Validate LLM-based solutions for accuracy, relevance, consistency, safety, latency, and task completion across realistic business scenarios
• Create test cases, evaluation datasets, and quality benchmarks for prompts, retrieval pipelines, orchestration flows, and end-user interactions
• Partner with AI engineers, product owners, and business stakeholders to define acceptance criteria and measurable quality standards
• Identify model failure modes, edge cases, hallucination risks, and workflow breakdowns, and recommend corrective actions
• Support automation of AI testing, monitoring, and quality reporting across development and production environments
• Test data flows, APIs, integrations, and system dependencies that support AI-enabled business processes
• Contribute to governance and release readiness by documenting defects, risks, test results, and quality decisions
• Monitor production feedback, user behavior, and operational metrics to help drive continuous improvement
• Help establish repeatable AI quality engineering practices, tooling, and controls for enterprise delivery

Required Qualifications:

• Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or related field
• 6+ years of experience in quality engineering, software testing, QA automation, or related technical roles
• Experience testing enterprise applications, APIs, data pipelines, or workflow-based systems
• Experience evaluating AI or ML-based systems, including prompt behavior, output quality, or model-driven workflows
• Strong understanding of test strategy, defect management, root cause analysis, and quality metrics
• Familiarity with automation frameworks, test management tools, and CI/CD-aligned quality processes
• Ability to work across technical and business teams to define and validate expected outcomes

Preferred Qualifications:

• Experience with LLM evaluation, prompt testing, RAG validation, or AI observability tools
• Familiarity with Python, SQL, APIs, or scripting for test automation and data validation
• Experience building synthetic datasets, golden test sets, or evaluation frameworks for AI use cases
• Exposure to responsible AI, model risk, privacy, or governance controls in enterprise settings
• Experience in financial services, wealth management, consulting, or other regulated environments

Core Competencies:

• Analytical rigor and attention to detail
• Structured testing and defect analysis
• Curiosity about model behavior and failure modes
• Cross-functional collaboration
• Clear communication of quality risks and trade-offs
• Focus on reliability, user trust, and measurable outcomes