Senior Technical Product Manager, Applied AI
Listed on 2026-05-18
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IT/Tech
AI Engineer (Applied/Software), Product Engineer
The Opportunity
Mattel Digital Studios (MDS) is a cross-functional division that leverages digital innovation to amplify Mattel’s iconic brands, expanding into digital gaming, interactive experiences, and emerging technologies. The MDS Tech organization serves as the technical foundation across this portfolio, building scalable systems, tools, and platforms that enable product teams to move quickly and deliver high-quality digital experiences. Working across multiple products and partners, the team focuses on unlocking the value of AI, data, and modern development frameworks to power personalization, content creation, and next-generation play experiences.
As part of this ecosystem, the Applied AI function sits at the intersection of product innovation and technical execution—unlocking new capabilities across creative workflows, internal tooling, and development pipelines.
What Your Impact Will BeAs a Senior Technical Product Manager, Applied AI, you will define, build, and scale AI-powered tools, workflows, and decision-support systems across Mattel Digital Studios. You will be accountable for identifying friction in cross-functional workflows—process misalignment, communication overhead, unreliable data, and stretched team bandwidth—and for translating that friction into a prioritized portfolio of AI solutions that measurably move the business.
You will manage a portfolio framed in three buckets — Quick Wins, Efficiency Gains, and Strategic Bets — with the strongest opportunities progressing from proof-of-concept into strategic pilot and broader MDS rollout. The scope spans workflow automation, internal tooling, creative and content-generation tools, and decision-support systems tied to real operational use cases.
Unlike traditional product roles, this position requires hands‑on technical execution. You will actively build prototypes, experiment with AI models and APIs, and develop working solutions; but success goes beyond prototyping—it is seeing opportunities through productization, rollout, stakeholder alignment, team enablement, and repeatability across disciplines. You will partner with MDS leadership and the Product, Engineering, Operations, and Creative teams, bringing external vendors where buying beats building.
This role is critical in ensuring that AI efforts are grounded in real business and user value, avoiding both strategy without execution and technology without clear application. You will also help flag and manage adoption risk—data quality, model accuracy and reliability, brand and creative integrity, and appropriate guardrails—partnering with the Office of AI and other governance stakeholders as needed.
This role reports to the MDS Technical Director and works cross-functionally across MDS.
Portfolio & Pain-Point Ownership- Own the applied AI roadmap from pitch to production — with direction and buy-in from MDS leadership, balancing speed, experimentation, and long‑term value creation.
- Identify and surface use cases and friction—assessing feasibility and scalability, translating them into high‑impact AI opportunities.
- Manage the opportunity portfolio—graduating the strongest proofs‑of‑concept into strategic pilots and broader MDS rollout.
- Translate business needs into AI‑powered tools, workflow automations, and decision‑support solutions, defining clear requirements, success metrics, adoption targets, and iteration plans.
- Continuously explore emerging AI capabilities and evaluate their application for internal tools, workflows, and content pipelines; apply them where operational impact, not novelty, justifies the work.
- Build prototypes, lightweight applications, automations, and decision‑support tools. Work hands‑on, using modern AI platforms — LLM APIs, multimodal models, agent frameworks, orchestration tools, and evaluation harnesses.
- Rapidly test and iterate on new ideas with a focus on measurable operational impact.
- Partner with engineering, platform, and external vendors to productize, harden, and scale successful prototypes—owning build‑vs‑buy judgment and seeing opportunities through to live deployment.
- Act as a bridge…
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