Vice President, Enterprise AI & Analytics

About the role

The Vice President, Enterprise AI and Analytics will lead Autodesk's enterprise AI and data strategy. Reporting to the CIO, this leader will own the AIDA domain and will serve as the primary architect of how Autodesk builds, governs, and compounds intelligence at enterprise scale.

Responsibilities

• Define and own Autodesk's enterprise intelligence architecture — the data foundations, agent infrastructure, and governance layer that sit above existing enterprise systems and connect them into a unified, reasoning whole.

• Establish and drive the enterprise data strategy, including governance, quality, classification, access controls, and retention across cloud, application, and security domains.

• Lead the transition from application-centric data silos toward a unified data foundation built on open standards, ensuring Autodesk's data remains portable, owned, and available for AI reasoning across the full organization.

• Define the framework for identifying where Autodesk's unique business logic — its decisions, rules, and workflows — lives inside vendor systems, and drive its extraction into open standards the company permanently owns.

• Collaborate with analytics domain leaders across the company to establish common practices, shared standards, and a consistent approach to data and AI that scales beyond any single team.

• Lead and accelerate the enterprise AI portfolio — moving active initiatives from pipeline through production with urgency and rigor, in close partnership with the business functions being served.

• Drive build vs. buy vs. partner decisions with discipline — leveraging vendor AI capabilities where appropriate while protecting investment in Autodesk-owned, differentiated intelligence.

• Create the working model for the full agent lifecycle — design, build, test, deploy, and maintain — creating the repeatable engineering discipline that makes agentic AI safe, scalable, and continuously improvable.

Qualifications

• Minimum of 15+ years in technology leadership, with a material portion spent owning enterprise AI, data platforms, or intelligent automation at scale — not just advising on them.

• A portfolio of AI programs that have moved well beyond pilots — shipped, in production, and delivering measurable business outcomes: productivity gained, cost reduced, decisions improved.

• Deep, hands-on fluency in modern data engineering and data architecture — data modeling, pipeline design, open table formats (Iceberg, Delta Lake), cloud-native data infrastructure, semantic and ontology layers, real-time and batch processing — combined with the ability to extend that foundation into agentic AI systems: LLM orchestration, RAG architectures, LLMOps, and multi-agent design patterns.

• A clear, tested point of view on enterprise AI vendor strategy: what to adopt, what to own, and how to avoid paying a premium for intelligence that should have been yours.

• Proven track record leading or rebuilding organizations through strategic transition — knows how to inherit a team, assess honestly, change what needs changing, and keep the best people through it.

• Leadership experience leading Data Science and Data Engineering functions at scale — not just as a technical practitioner, but as the leader accountable for the team, the platform, and the outcomes.

• Executive presence that works at every altitude — can set technical architecture with a principal engineer in the morning and brief the board on AI strategy in the afternoon, and be credible in both rooms.

• Proven ability to lead globally distributed, multi-disciplinary teams across time zones and functions — with empathy for the people and accountability for the outcomes.

• Comfort with ambiguity — this leader creates clarity for others, not the other way around.

Skills

• Strategic thinking and the ability to translate strategy into actionable plans.

• Strong communication skills, both written and verbal, to articulate complex technical concepts to non-technical stakeholders.

• Ability to manage multiple projects and priorities simultaneously.

• Experience with AI ethics, fairness, and bias mitigation.

• Experience with regulatory compliance and data privacy.

Benefits

Autodesk offers a comprehensive benefits package, including health and financial benefits, time away, and everyday wellness. For U.S.-based roles, the starting base salary ranges from $270,000 to $396,000, with additional compensation options such as annual cash bonuses, commissions for sales roles, stock grants, and a benefits package.

Pay

Salary is one part of Autodesk’s competitive compensation package. For U.S.-based roles, we expect a starting base salary between $270,000 and $396,000. Offers are based on the candidate’s experience and geographic location, and may exceed this range.

Schedule

Flexible work arrangements are available to support a healthy work-life balance.

Equal Employment Opportunity

Autodesk is committed to providing equal employment opportunities to all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status, or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law.