Technical Product Manager - Enterprise GenAI/ML Platform

About the role

Collaborative. Respectful. A place to dream and do. These are just a few words that describe what life is like at Toyota. As one of the world's most admired brands, Toyota is growing and leading the future of mobility through innovative, high-quality solutions designed to enhance lives and delight those we serve. We're looking for talented team members who want to Dream. Do. Grow. with us. An important part of the Toyota family is Toyota Financial Services (TFS), the finance and insurance brand for Toyota and Lexus in North America. While TFS is a separate business entity, it is an essential part of this world-changing company- delivering on Toyota's vision to move people beyond what's possible. At TFS, you will help create best-in-class customer experience in an innovative, collaborative environment. Toyota does not offer support or sponsorship of job applicants for employment-based visas or any other work authorization for this role now or in the future. You must have the right to work in the United States and not require Toyota support or sponsorship for immigration-related employment (e.g., H-1B, O-1, E-3, H-1B1, TN, F-1 OPT, F-1 STEM OPT, F-1 CPT, TN, 'job flexibility benefits' (also known as I-140 or Adjustment of Status portability), etc. now or in the future. You should not apply for this role if you will require Toyota to assist with immigration support or sponsorship now or in the future. This position is an onsite role based in Plano, TX Who We're Looking For The TFS Enterprise Platforms team is seeking a highly motivated Product Manager, Enterprise GenAI/ML Platform to lead the strategy, roadmap, and delivery of enterprise AI and machine learning platform capabilities. In this role, you will drive the development of a scalable internal platform that enables engineering, data, and business teams to build, deploy, and govern AI-powered solutions efficiently and responsibly across the organization. As a Product Manager for the Enterprise GenAI/ML Platform, you will work closely with engineering teams, architects, data scientists, security, risk, and cross-functional business stakeholders to identify high-value opportunities and define platform capabilities that accelerate adoption of AI and ML across the enterprise. Your expertise in platform product management, cloud technologies, AI/ML lifecycle management, and modern software delivery practices will enable you to define and execute a clear product vision for reusable, secure, and scalable AI services. This role requires a strong technical product mindset and fluency in Amazon Bedrock , Amazon SageMaker , and enterprise AI/ML platform patterns, including LLM workflows, retrieval-augmented generation, prompt management, model access, evaluation frameworks, MLOps, governance, and platform APIs . The ideal candidate is passionate about building internal platforms that improve developer experience, reduce time to value, and establish responsible AI guardrails at scale.

Responsibilities

• Own and manage the full product lifecycle for the Enterprise GenAI/ML Platform, from vision and strategy through design, development, release, adoption, and continuous improvement, ensuring alignment with business goals and enterprise technology strategy.
• Define and drive the roadmap for reusable AI/ML platform capabilities, including model access, prompt orchestration, RAG enablement, evaluation tooling, model monitoring, MLOps workflows, and self-service platform experiences.
• Partner with engineering, architecture, data science, security, legal, compliance, and business stakeholders to gather requirements and prioritize platform features that improve scalability, governance, usability, and developer productivity.
• Lead backlog refinement and roadmap prioritization using agile methodologies, ensuring timely delivery of high-value features that support both business outcomes and technical platform maturity.
• Drive product decisions around Amazon Bedrock and Amazon SageMaker usage patterns, including foundation model access, prompt-based applications, model development workflows, deployment approaches, and lifecycle management.
• Define platform capabilities that support LLM application patterns , including prompt management, retrieval-augmented generation, embeddings-based solutions, evaluation pipelines, and secure model consumption.
• Partner with technical teams to shape MLOps and operational processes for training, deployment, versioning, experimentation, monitoring, rollback, and retraining of models and AI services.
• Establish clear success metrics and KPIs for platform adoption, model quality, latency, reliability, cost efficiency, developer experience, and business impact.
• Champion best practices in platform product management, cloud-native architecture, automation, internal developer experience, and AI/ML service enablement.
• Ensure enterprise AI capabilities align with requirements for Responsible AI , security, privacy, compl

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