Lead Quality Engineer AI Enablement
Mattel · East Aurora, NY
- Level
- Manager
- Team
- Quality
- Degree
- Required
- Experience asked
- 5+ years
- Industry
- Industrial
- Posted
- 17 days ago
The role in 30 seconds
A management quality role at Mattel (industrial) in East Aurora, NY.
- They ask for
- 5+ years · degree required
- Tools it names
- Validation (IQ/OQ/PQ), Automation, Tooling
Read from the posting. The full description is below.
From the plant jobs report · week of October 19, 2026
Quality Engineer roles in New York: typical posted base $86k–$126k.
Median of the low and high ends of 18 live postings that list pay, out of 26 quality engineer openings in New York, read from manufacturers' own careers sites.
New York plant jobs report →Pay by team and state →What moves pay →
How this role compares
Against 25 other live quality postings in New York.
- Base pay
- Not listed in this posting
- Experience asked
- Less than usual (5+ vs 6+)
Typical $86k–$126k, from 18 postings that list pay.
Similar roles usually ask 6+ years.
Skills these teams ask for most
- Root cause 73%
- Six Sigma 50%
- AS9100 46%
- SPC 46%
- Lean 38%
- PPAP 35%
✓ = this posting asks for it too. % = share of similar postings that mention it.
Stands out: this posting asks for Tooling, which few similar roles mention. If you have it, lead with it.
At a glance
Pulled from the posting text. If it's not listed here, the posting didn't say.
How to get in at this plant
Five moves over a week or two. The first one takes ten minutes.
- 1
Pick 2–3 people on the Quality team at Mattel
Engineers who joined in the last year or two reply the most. Use the team search on this page to find them.
- 2
Send a short, curious note
One real question about their work. No favors yet. Each person gets a different note, written for this role.
- 3
Turn a reply into a short call
Questions worth asking about this team:
- What does a normal week look like on your team?
- Which standards drive the work here: ISO 13485, IATF 16949, AS9100?
- How much of the job is customer complaints versus prevention?
- How did you land the job? What stood out in your interviews?
- 4
Apply with someone vouching for you
If the call went well, ask whether they’d pass your résumé to the hiring manager. Send your résumé link, apply that day, and let them know.
- 5
Bring proof to the interview
One page of before-and-after numbers from projects you led: scrap, OEE, cycle time, cost. Plant managers hire on results.
Full description from MattelAs posted on their careers site.ShowHide
requirements
for RAG, RAG+Build, agentic workflows, predictive models, decision support, workflow automation, and scalable platform capabilities.
- ✓Define the data, system, and knowledge inputs required 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 questions related to pricing or elasticity, cost increases, sustainability or packaging choices, consumer response, risk, ROI, 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, SME review logs, readiness scorecards, and handoff packages.
- ✓Define practical quality gates for AI-enabled workflows, including evidence requirements, citation expectations, answer-quality criteria, regression testing, exception handling, escalation rules, and release readiness.
- ✓Help prevent fragmented AI solutions by identifying 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 ROI.
Show full description ↓Show less ↑
The Opportunity
Mattel is currently seeking a Quality Engineer, Applied AI Solutions & Enablement in East Aurora, NY. This role will help Global Quality & Safety solve complex business and Quality problems by translating expert knowledge, process pain points, and decision needs into working prototypes, build-ready requirements, scalable solution designs, validation plans, and governed handoff packages.
The role requires a hands-on solution builder who can move quickly from problem to prototype, prove value with stakeholders, and then partner with GTO, the Office of AI, data teams, and external vendors to scale the right solutions responsibly. The person does not need to be the final production engineer for every solution, but they must be comfortable shaping technical direction, testing outputs, maintaining vendor relationships, and ensuring prototypes can become supportable enterprise capabilities.
The initial focus will center on advancing the Quality organization through AI-enabled decision support, knowledge access, and workflow transformation. The role will also support broader Quality AI initiatives spanning AI readiness, scalable solution design, intelligent automation, predictive insights, and experimentation to help build reusable capabilities across Global Quality.
The ideal candidate can operate between business process, Quality Engineering, data, AI, technology delivery, executive communication, and partner management. They must be able to build clarity from ambiguity, create compelling presentations and demos, align internal teams, manage vendor inputs, and convert prototypes into plans that can scale across Global Quality.
What Your Impact Will Be
- •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 closely 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 productive 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 clear 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 SMEs 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, with an initial emphasis on NPD 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
What We’re Looking For
- •Bachelor’s degree in Engineering, Quality, Data Analytics, Information Systems, Product Development, Business Process Management, or a related field; equivalent practical experience will be considered.
- •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 relationshi