Business Strategist, AI Foundation Models

Autodesk
24 LocationsPosted 25 April 2026

Job Description

Job Requisition ID # 26WD97210 L'affichage de poste en français suivra / The French job posting follows. Position Overview Autodesk is building the next generation of AI capabilities that will transform how customers design and make. The Foundation Models team develops AI technologies that operate across Autodesk’s platform and business units. This role provides the analytical foundation needed to guide adoption, monetization, cost modeling, and strategic planning for these AI investments. You will apply structured problem-solving, financial modeling, usage analytics, and cost analysis, including inference COGS and GPU economics, to inform business decisions. Your work will clarify how foundational models scale, how they affect Autodesk’s economics, and how the company should prioritize investment and deployment across multiple product areas. The successful candidate will operate at the center of Autodesk’s AI transformation, shaping business strategy and analytics that inform AI development, technology roadmaps, and long-term priorities. They will develop structured strategic frameworks, adoption and impact forecasts, and decision-support insights that guide Autodesk’s AI portfolio and enable leadership alignment across industry groups and executive forums. Location : We are open to candidates in Portland, Oregon, Canada and the United Kingdom Responsibilities Build analytical and financial models that quantify the business impact of AI capabilities across Autodesk’s platform and industry groups, including Architecture, Engineering & Construction, Product Design & Manufacturing, and Media & Entertainment Develop forecasts for AI adoption, usage, revenue influence, and long-term planning Construct business cases and decision-ready analysis to guide investment, prioritization, and leadership reviews Model and optimize inference cost economics (COGS), including GPU utilization, cloud strategy, and scaling drivers Translate product telemetry into insights supporting monetization, pricing, and cross-industry growth opportunities Create executive- and Board-ready presentations, narratives, and slide materials that communicate strategic recommendations, investment plans, and business priorities with clarity and impact Contribute to building repeatable dashboards, reporting frameworks, and tools to enable data-driven execution across Product, Finance, and Engineering teams Minimum Qualifications Bachelor’s degree in a relevant field (e.g., Engineering, Data Science, Statistics, Computer Science, Economics) or equivalent experience 5 years in business strategy, analytics, management consulting, or a similarly analytical role Strong financial modeling and analytical skills (Excel required; SQL/Python familiarity preferred) Ability to create structured, executive-ready presentations and strategic narratives (Management consulting-style PPT decks) Demonstrated ability to operate in ambiguous environments and build frameworks from scratch Strong communication skills with the ability to distill complexity into clarity Preferred Qualifications MBA or relevant graduate degree Management consulting experience (2–3 years) Experience in SaaS economics, cloud cost analysis, or AI/ML-driven products Familiarity with GPU and inference cost structures Background in subscription analytics or monetization strategy Experience with AI agents and API-driven business models ----------------------------------------------------------------------------------------------------------------------------------------------- Aperçu du poste Autodesk développe la prochaine génération de capacités en intelligence artificielle qui transformeront la façon dont les clients conçoivent et fabriquent. L’équipe des modèles fondamentaux développe des technologies d’IA qui s’intègrent à l’ensemble de la plateforme et des unités d’affaires d’Autodesk. Ce rôle fournit la base analytique nécessaire pour orienter l’adoption, la monétisation, la mo ... (truncated, view full listing at source)
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