Senior Technical Product Manager, Applied AI - Mattel Digital Studio

Mattel•El Segundo, CA

13d

About The Position

Mattel Digital Studios (MDS) is a division focused on digital innovation, expanding Mattel's brands into gaming, interactive experiences, and emerging technologies. The MDS Tech organization provides the technical foundation for this portfolio, building scalable systems, tools, and platforms. The Applied AI function within MDS focuses on unlocking new capabilities across creative workflows, internal tooling, and development pipelines using AI, data, and modern development frameworks. This role is responsible for defining, building, and scaling AI-powered tools, workflows, and decision-support systems across MDS. The goal is to identify and address friction in cross-functional workflows, such as process misalignment, communication overhead, unreliable data, and team bandwidth limitations, by developing a prioritized portfolio of AI solutions. These solutions will be categorized into Quick Wins, Efficiency Gains, and Strategic Bets, with the strongest opportunities progressing from proof-of-concept to pilot and broader rollout. The scope includes workflow automation, internal tooling, creative and content-generation tools, and decision-support systems. This role requires hands-on technical execution, including building prototypes, experimenting with AI models and APIs, and developing working solutions. Success involves productization, rollout, stakeholder alignment, team enablement, and repeatability. The role collaborates with MDS leadership, Product, Engineering, Operations, and Creative teams, and may involve external vendors. It ensures AI efforts are grounded in business and user value, avoiding strategy without execution or technology without clear application. The role also manages adoption risks related to data quality, model accuracy, brand integrity, and appropriate guardrails, partnering with the Office of AI and other governance stakeholders. This position reports to the MDS Technical Director and works cross-functionally within MDS.

Requirements

Bachelor’s degree in Computer Science, Engineering, Product Design, or related field (or equivalent experience).
5–8+ years of experience in product management, engineering, or technical roles, with a demonstrated track record of personally shipping internal tools, automations, and cross-functional operational improvements.
Hands-on experience building AI workflows and automations using LLM APIs, multimodal models, agent frameworks, and orchestration tools (e.g., OpenAI, Claude, LangChain, Python-based pipelines, Retool, low-code automation, etc.).
Demonstrated ability to take an AI solution from prototype through productization and rollout — including stakeholder alignment, enablement, and measuring business impact post-deployment.
Strong product and operator mindset, with the ability to diagnose workflow pain points and connect user needs and business goals to technical solutions.
Experience working cross-functionally with production, engineering, design, creative, and business stakeholders.
Strong problem-solving skills, with a bias toward action and rapid iteration.
Ability to operate in ambiguity and navigate emerging technology landscapes.
Strong communication and storytelling skills, with the ability to influence across technical and non-technical audiences.
Demonstrated curiosity and growth mindset, staying current with rapidly evolving AI capabilities—including awareness of responsible-use considerations.

Nice To Haves

Masters in Computer Science or related field preferred.

Responsibilities

Define, build, and scale AI-powered tools, workflows, and decision-support systems across Mattel Digital Studios.
Identify friction in cross-functional workflows (process misalignment, communication overhead, unreliable data, stretched team bandwidth) and translate it into a prioritized portfolio of AI solutions.
Manage a portfolio of AI solutions framed in three buckets: Quick Wins, Efficiency Gains, and Strategic Bets.
Progress the strongest opportunities from proof-of-concept into strategic pilot and broader MDS rollout.
Develop AI solutions for workflow automation, internal tooling, creative and content-generation tools, and decision-support systems tied to real operational use cases.
Actively build prototypes, experiment with AI models and APIs, and develop working solutions.
See opportunities through productization, rollout, stakeholder alignment, team enablement, and repeatability.
Partner with MDS leadership, Product, Engineering, Operations, and Creative teams, and bring in external vendors where buying beats building.
Ensure AI efforts are grounded in real business and user value.
Flag and manage adoption risks, including data quality, model accuracy and reliability, brand and creative integrity, and appropriate guardrails.
Partner with the Office of AI and other governance stakeholders as needed.
Own the applied AI roadmap from pitch to production, balancing speed, experimentation, and long-term value creation.
Identify and surface use cases and friction, assessing feasibility and scalability, and translating them into high-impact AI opportunities.
Manage the opportunity portfolio, graduating 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 AI capabilities where operational impact, not novelty, justifies the work.
Build prototypes, lightweight applications, automations, and decision-support tools.
Work hands-on using modern AI platforms like LLM APIs, multimodal models, agent frameworks, and orchestration tools.
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.
Own build-vs-buy judgment and see opportunities through to live deployment.
Act as a bridge between MDS leadership, Product, Engineering, Operations, and Creative teams to identify and unlock AI opportunities.
Secure leadership buy-in, drive alignment across stakeholders on priorities, and translate ambition into crisp execution plans.
Enable teams through reusable tools, workflow patterns, playbooks, and training that make adoption repeatable across disciplines.
Collaborate with external partners (e.g., OpenAI) to accelerate internal capability building.
Spearhead vendor evaluation and integration.
Manage adoption risks (data quality, compliance, hallucinations, over-reliance, brand and creative integrity), setting guardrails with the Office of AI and consulting with legal and privacy teams.
Define success metrics per opportunity (productivity, quality, cost, effectiveness) and report portfolio impact on a regular cadence.