Technical Product Manager - Enterprise GenAI/ML Platform

Toyota North America • Plano, TX

1d • Onsite

About The Position

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.

Requirements

• 8+ years of relevant experience in product management, technical platform delivery, cloud technologies, or enterprise software implementations.
• 5+ years of product management experience with a focus on technical platforms, internal platforms, cloud platforms, AI/ML products, or developer-facing capabilities.
• Proven experience defining product vision, roadmaps, and requirements for complex technical platforms in a fast-paced, agile environment.
• Strong technical understanding of generative AI, machine learning platforms, and LLM-based application patterns, including prompt workflows, RAG, evaluation, model lifecycle, and platform APIs.
• Working knowledge of Amazon Bedrock and Amazon SageMaker, including their role in enterprise GenAI/ML platform architecture and delivery.
• Experience collaborating with engineering, architecture, data science, security, and governance stakeholders to deliver scalable enterprise capabilities.
• Understanding of MLOps concepts, including model development, deployment pipelines, monitoring, versioning, retraining, and operational lifecycle management.
• Familiarity with enterprise concerns related to Responsible AI, model governance, privacy, security, compliance, and risk controls.
• Strong communication skills with the ability to articulate technical concepts, platform strategy, and business value across diverse audiences.
• Bachelor’s Degree in Information Systems, Computer Science, Engineering, Data Science, or a related field.

Nice To Haves

• Master’s Degree in Computer Science, Software Engineering, Data Science, or a related field.
• Experience building or scaling enterprise GenAI/ML platforms or other horizontal internal platforms.
• Hands-on experience with retrieval-augmented generation, prompt engineering, model evaluation frameworks, embeddings, vector search, or LLM application architecture.
• Experience with enterprise AWS environments and cloud-native services supporting AI/ML workloads.
• Familiarity with model safety controls, AI guardrails, and governance frameworks for regulated or large-scale enterprise environments.
• Demonstrated success enabling internal teams through reusable APIs, templates, self-service tooling, and strong developer experience practices.
• Experience supporting cost, performance, and adoption optimization for AI/ML platform services.

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, compliance, model governance, access controls, auditability, and risk management.
• Communicate product strategy, roadmap, priorities, and measurable outcomes to technical teams, business stakeholders, and leadership, translating complex AI/ML concepts into clear business value.
• Support vendor and partner engagement related to AI/ML platform capabilities, tooling, integrations, and cloud ecosystem solutions where applicable.

Benefits

• A work environment built on teamwork, flexibility, and respect
• Professional growth and development programs to help advance your career, as well as tuition reimbursement
• Team Member Vehicle Purchase Discount.
• Toyota Team Member Lease Vehicle Program (if applicable).
• Comprehensive health care and wellness plans for your entire family
• Toyota 401(k) Savings Plan featuring a company match, as well as an annual retirement contribution from Toyota regardless of whether you contribute
• Paid holidays and paid time off
• Referral services related to prenatal services, adoption, childcare, schools, and more
• Tax Advantaged Accounts (Health Savings Account, Health Care FSA, Dependent Care FSA)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior