Quality Engineering, AI Validation Manager

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Shyft6

SiteLinkedInTodas as Vagas

201 - 500 funcionários

Fundada em 2019

👥 RH Tech

🎯 Recrutamento

🤝 B2B

HR Tech • Recruitment • B2B

A Shyft6 é uma parceira confiável para empresas inovadoras, especializada em soluções de força de trabalho que abrangem recrutamento e seleção, gestão de força de trabalho e estratégia de capital humano. Com mais de 26 anos de experiência combinada, a Shyft6 oferece uma ampla gama de serviços, incluindo gestão de fornecedores de força de trabalho contingente, terceirização de processos de recrutamento, aumento de pessoal, busca de executivos e folha de pagamento em múltiplos estados. Seu foco é capacitar as organizações por meio do desenvolvimento eficaz da força de trabalho e gestão de projetos, garantindo a entrega bem-sucedida e a aquisição de talentos qualificados.

Descrição

• 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. • 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. • 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. • 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. • 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.

🎯 Requisitos

• 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.

🏖️ Benefícios

• Salary plus a performance-based bonus