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Mattel

Global toy and family entertainment company.

Lead Quality Engineer AI Enablement

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeEast Aurora, NY, USA$105k - $120k /yr

About the Job

Requirements

  • A bachelor's degree in Engineering, Quality, Data Analytics, Information Systems, Product Development, Business Process Management, or a related field, or equivalent practical experience.
  • At least 5 years of experience in Quality, Product Development, Engineering, Compliance, Operations, Business Analysis, AI enablement, data/analytics, technology delivery, solution consulting, or process transformation.
  • Demonstrated ability to solve business problems, create working prototypes or proofs of concept, test value quickly, and translate successful pilots into scalable implementation plans.
  • Experience partnering with IT, digital, data, platform, architecture, cybersecurity, or enterprise technology teams to move prototypes toward governed, supportable solutions.
  • Experience managing or coordinating vendor work, including requirements, demos, pilots, deliverables, tradeoff evaluation, and relationship management.
  • Strong presentation and storytelling skills, including the ability to create executive-ready narratives, demos, business cases, roadmaps, and decision materials.
  • Practical understanding of AI-enabled solution patterns such as retrieval-augmented generation (RAG), AI agents, workflow automation, human-in-the-loop review, model evaluation, and validation/testing of AI outputs.
  • Ability to learn complex business processes quickly and convert expert knowledge into structured workflows, requirements, decision logic, validation plans, and scalable solution concepts.
  • Experience working with cross-functional teams across Quality, Engineering, Product Development, Regulatory, Packaging, Manufacturing, IT, data/analytics, and/or external partners.
  • Ability to define source-of-truth requirements, metadata needs, taxonomy, access considerations, feedback loops, and governance controls for knowledge-heavy workflows.
  • Analytical and systems-thinking skills to connect process steps, data sources, decisions, controls, risks, business outcomes, and scaling constraints.
  • Comfort working with evolving tools and technologies while maintaining focus on business value, risk, governance, repeatability, and adoption.

Responsibilities

  • Solve Quality and business problems by framing the issue, identifying the decision or workflow need, designing practical solution paths, and building or coordinating rapid prototypes that demonstrate value.
  • Rapidly prototype AI-enabled tools, workflow automations, dashboards, document-generation experiences, agentic workflows, decision-support models, and knowledge-retrieval solutions using approved Mattel tools, data sources, and partner capabilities.
  • Partner with GTO, the Office of AI, data teams, cybersecurity, architecture, and approved technology partners to define scalable solution paths, data access needs, integration requirements, support models, and production-readiness criteria.
  • Build and maintain vendor relationships, including scoping pilot work, preparing requirements, evaluating demos, comparing solution options, tracking deliverables, and ensuring external partners understand Quality’s business needs and constraints.
  • Create presentations, demos, business cases, roadmaps, and executive-ready narratives that explain the problem, prototype, value, risk, investment need, scaling path, and decision required.
  • Partner with Quality subject-matter experts to map core workflows, decision points, systems, artifacts, handoffs, exceptions, and approval gates across Quality and Safety processes.
  • Convert expert process knowledge into AI-ready task context, knowledge context, execution context, instruction context, validation criteria, and human-in-the-loop requirements.
  • Lead process discovery and solution enablement for priority use cases, initially emphasizing New Product Development workflows such as ICR, DSP, CR/FPR, tooling, engineering pilots, production pilots, PCD, PRD, hazard review, labeling, packaging, reliability, lab testing, and missing-parts risk.
  • Translate Quality use cases into build-ready requirements for RAG, RAG+Build, agentic workflows, predictive models, decision support, workflow automation, and scalable platform capabilities.
  • Define data, system, and knowledge inputs for Quality AI capabilities, including Veeva, Polarion, Windchill, Agile PLM, SharePoint, Teams, GCP/BigQuery, product data, lab/testing information, manufacturing information, consumer feedback, social signals, and other approved datasets.
  • Support business tradeoff and impact modeling, including pricing or elasticity, cost increases, sustainability or packaging choices, consumer response, risk, return on investment, and scale economics.
  • Build and maintain process maps, source inventories, metadata and taxonomy requirements, prompt and agent specifications, workflow diagrams, golden question sets, test cases, subject-matter-expert review logs, readiness scorecards, and handoff packages.
  • Define quality gates for AI-enabled workflows, including evidence requirements, citation expectations, answer-quality criteria, regression testing, exception handling, escalation rules, and release readiness.
  • Identify repeatable patterns, shared data needs, reusable components, and opportunities to consolidate disconnected pilots into scalable platform capabilities.
  • Measure and communicate outcomes such as time saved, reduced rework, improved decision visibility, readiness progress, workflow reliability, risk reduction, adoption, and return on investment.

Desired Qualifications

  • Experience in toys, consumer products, manufacturing, product safety, regulatory compliance, product development, or Quality Engineering.
  • Familiarity with New Product Development gates and deliverables such as ICR, DSP, CR/FPR, PCD, PRD, functional specifications, hazard analysis, labeling forms, lab testing, engineering pilots, production pilots, and final production start.
  • Familiarity with enterprise Quality/Product systems such as Veeva, Polarion, Windchill, Agile PLM, GCP/BigQuery, SharePoint, Teams, or similar systems.
  • Experience building, specifying, or validating AI-enabled tools, agents, document-generation workflows, knowledge bases, workflow automations, dashboards, data apps, or analytics products.
  • Experience with process mapping, business architecture, product ownership, solution design, design thinking, process mining, knowledge management, ontology/taxonomy design, context graphs, knowledge graphs, or requirements analysis.
  • Experience defining acceptance criteria, testing plans, golden question sets, regression tests, quality gates, audit logs, or validation frameworks for digital or AI-enabled systems.
  • Experience working with consumer feedback, product reviews, service transcripts, social signals, manufacturing data, lab test data, or product quality datasets.
  • Ability to work hands-on with prototypes, prompts, data extracts, workflow tools, vendor demos, and presentation materials while also creating executive-level recommendations.

About the Company

Mattel

Global toy and family entertainment company.

Mattel is a global play and family entertainment company that owns iconic brands such as Barbie, Hot Wheels, Fisher-Price, and UNO, offering toys, content, consumer products, digital experiences, and live events. Its products come to life through brands and franchises that create physical toys, media content, and themed experiences, often via owned properties or licensed partnerships with entertainment companies. Mattel stands out with a diversified catalog of enduring franchises and cross-category play experiences that combine toys with media and consumer products. Its goal is to empower generations to explore the wonder of childhood and reach their full potential by treating play as a key path to the future, engaging consumers through authentic franchise brands and immersive experiences.

Company size
10,001+
Company stage
IPO
Headquarters
El Segundo, CA
Founded
1945

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