Quality Engineering & AI Validation Manager
14 days ago
New York
Job Description This is a remote position. Quality Engineering & AI Validation Manager Reporting to Head of Engineering, leads Accordion's centralized Quality Engineering and AI Validation function across software delivery pods. Owns the quality operating model, release-readiness standards, test strategy, AI validation framework, and quality metrics used to support both conventional software and AI-enabled solutions. Ensures quality is designed into delivery from the start, not inspected in at the end. Key Responsibilities Quality Strategy & Governance · Define the firm-wide quality strategy, release gates, and validation standards across development pods. · Establish a risk-based quality model for traditional software and AI-enabled workflows. · Define when pod-level validation is sufficient and when independent QA validation is required. AI Validation Leadership · Build and operationalize the QA approach for AI-led products, including benchmark datasets, scoring rubrics, regression comparisons, and grounded-output validation. · Establish testing expectations for instruction adherence, consistency, business correctness, control compliance, and hallucination risk. · Partner with Engineering and Product leaders on quality implications of prompt, model, workflow, and tooling changes. Team Leadership · Lead and develop quality engineers, AI quality analysts, and domain-oriented QA resources. · Improve the maturity of automation, evaluation routines, test evidence standards, and release discipline. · Create a scalable central model that supports pods without becoming a bottleneck. Finance & Risk Alignment · Partner with Finance and practice SMEs to ensure solutions are validated against real business use, materiality, and control expectations. · Ensure high-risk workflows receive the right level of domain review before production release. Production Quality · Define the framework for production quality monitoring, including escaped defects, output-quality degradation, reviewer overrides, and control failures. · Create visibility into quality trends, readiness, and recurring failure patterns for Engineering and leadership. RequirementsRequired Qualifications · 8+ years of QA, software testing, or quality engineering experience, including team leadership. · Experience building test strategy, release-readiness processes, and automation programs in modern software environments. · Experience supporting AI-enabled applications, workflow automation, data products, or decision-support systems. · Strong understanding of functional, integration, regression, API, and data validation approaches. · Ability to translate business-critical finance workflows into quality controls and release criteria. · Strong communication skills and credibility with Engineering, Product, and business stakeholders. · Bachelor's degree preferred. You Are · Structured, pragmatic, and highly credible. · Comfortable asking tough questions about readiness, risk, and evidence. · A builder of quality systems and operating models. · Fluent in both engineering quality and business impact. · Focused on trust, traceability, and scalable execution. Benefits Salary plus a performance-based bonus Actual compensation packages are determined by evaluating a wide array of factors unique to each candidate, including but not limited to skill set, years and depth of experience, education, certifications, cost of labor, and internal equity.