Manager - AI Value Realization

toyota; Plano (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

Toyota's Enterprise AI Department seeks a passionate AI Value Realization Manager to make the AI portfolio tangible by linking objectives, adoption, utilization, and lifecycle cost to measurable business outcomes.

You will own end‑to‑end cost visibility across AI products and tools, design showback or chargeback, unit economics, and concise executive reporting, partnering with finance, procurement, and engineering to optimize budgets and value realization.

Qualifications

• Bachelor’s degree in computer science, AI, data science, engineering, mathematics, finance, statistics, business, or equivalent practical experience.
• At least 6 years of experience in AI, software, cloud, data platforms, automation, FinOps engineering, or a related discipline, including leadership of complex enterprise initiatives and technical teams.
• Experience building cost visibility, allocation, forecasting, optimization, chargeback or showback, unit economics, dashboards, or analytical products for cloud, software, data, or AI platforms.
• Proficiency in Python, Java, JavaScript, C++, or

Responsibilities

• Develop an AI investment measurement strategy linking objectives, adoption, utilization, technical performance, and lifecycle cost to measurable business outcomes.
• Maintain a portfolio view of custom products and purchased software from intake through retirement, including ownership, status, dependencies, cost, utilization, risk, and realized value.
• Create reusable business‑case, benefit‑tracking, and review methods with evidence‑based checkpoints for pilot, production, scale, renewal, consolidation, and retirement.
• Partner with business and product leaders to define baselines, success measures, evidence plans, and high‑impact roadmaps; identify solutions to optimize, renegotiate, consolidate, replace, or retire.
• Provide concise executive reporting and lead a high‑performing engineering team through clear goals, coaching, and development.
• Establish end‑to‑end cost visibility across custom AI products and commercial tools, including cloud infrastructure, model usage, data, observability, licenses, consumption fees, vendor services, and support.
• Design allocation, tagging, showback or chargeback, forecasting, and anomaly detection capabilities that attribute costs to products, use cases, environments, teams, and outcomes.
• Develop unit economics‑such as cost per user, transaction, workflow, model call, token, or outcome‑to guide architecture, model, and vendor decisions.
• Partner with finance, procurement, and engineering to improve budgets, forecasts, vendor management, license utilization, and total cost of ownership.
• Partner with AI Engineering, Strategy & Trust teams providing data that helps define standards on optimization, agents, infrastructure, licenses, and consumption plans.
• Lead the design, delivery, and operation of production‑quality data services, dashboards, APIs, automation, and pipelines for AI value and cost management.
• Combine cloud billing, model and API usage, platform telemetry, product analytics, financial data, and business outcomes into trusted reporting products.
• Embed value, cost, usage, and benefit evidence into delivery, procurement, workflow, and monitoring systems.
• Partner with AI Engineering & Strategy teams on decisions related to platform value, cost, performance, risk, and portability.

Skills

Python

Java

JavaScript

C++

Leadership

Cloud platforms

Education

Bachelor's degree in CS or related field

Job description

Overview

Who we are

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.

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, '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.

Who we’re looking for

Toyota’s Enterprise AI Department is looking for a passionate and highly motivated AI Value Realization Manager .

The primary responsibility of this role is to make the value, cost, utilization, adoption, and performance of Toyota’s AI portfolio visible and actionable by connecting custom AI products and purchased software to measurable business outcomes, lifecycle cost, and benefits.

Reporting to the Senior Manager, Enterprise AI Value & Cost Transparency, this leader will manage a hands‑on engineering function spanning AI economics, FinOps, utilization analytics, portfolio measurement, and executive decision support. The role partners across business, engineering, finance, procurement, and vendor management to select, operate, govern, and demonstrate the value of AI solutions.

This position is based in Plano Texas. The selected candidate will be expected to reside within a commutable distance of this location.

What you’ll be doing

AI value and portfolio transparency

Develop an AI investment measurement strategy linking objectives, adoption, utilization, technical performance, and lifecycle cost to measurable business outcomes.

Maintain a portfolio view of custom products and purchased software from intake through retirement, including ownership, status, dependencies, cost, utilization, risk, and realized value.

Create reusable business‑case, benefit‑tracking, and review methods with evidence‑based checkpoints for pilot, production, scale, renewal, consolidation, and retirement.

Partner with business and product leaders to define baselines, success measures, evidence plans, and high‑impact roadmaps; identify solutions to optimize, renegotiate, consolidate, replace, or retire.

Provide concise executive reporting and lead a high‑performing engineering team through clear goals, coaching, and development.

AI cost transparency and optimization

Establish end‑to‑end cost visibility across custom AI products and commercial tools, including cloud infrastructure, model usage, data, observability, licenses, consumption fees, vendor services, and support.

Design allocation, tagging, showback or chargeback, forecasting, and anomaly detection capabilities that attribute costs to products, use cases, environments, teams, and outcomes.

Develop unit economics‑such as cost per user, transaction, workflow, model call, token, or outcome‑to guide architecture, model, and vendor decisions.

Partner with finance, procurement, and engineering to improve budgets, forecasts, vendor management, license utilization, and total cost of ownership.

Partner with AI Engineering, Strategy & Trust teams providing data that helps define standards on optimization, agents, infrastructure, licenses, and consumption plans.

Engineering platforms and automation

Lead the design, delivery, and operation of production‑quality data services, dashboards, APIs, automation, and pipelines for AI value and cost management.

Combine cloud billing, model and API usage, platform telemetry, product analytics, financial data, and business outcomes into trusted reporting products.

Embed value, cost, usage, and benefit evidence into delivery, procurement, workflow, and monitoring systems.

Partner with AI Engineering & Strategy teams on decisions related to platform value, cost, performance, risk, and portability.

What you bring

Bachelor’s degree in computer science, AI, data science, engineering, mathematics, finance, statistics, business, or a related field, or equivalent practical experience.

At least 6 years of experience in AI, software, cloud, data platforms, automation, FinOps engineering, or a related discipline, including leadership of complex enterprise initiatives and technical teams.

Experience building cost visibility, allocation, forecasting, optimization, chargeback or showback, unit economics, dashboards, or analytical products for cloud, software, data, or AI platforms.

Proficiency in Python, Java, JavaScript, C++, or