Vice President, Enterprise AI & Analytics

Autodesk•San Francisco, CA

4d•Remote

About The Position

Autodesk is seeking a Vice President Enterprise AI and Analytics to lead the company's enterprise AI and data strategy. Reporting to the CIO, this leader will own the AIDA (Enterprise AI, Data & Automation) domain and will serve as the primary architect of how Autodesk builds, governs, and compounds intelligence at enterprise scale. This leader will have full latitude to influence and shape the organization, operating model, and technical architecture needed to execute that vision. There is real capability here and real work in flight. What this leader brings is the strategic clarity, architectural conviction, and organizational authority to take that capability to a fundamentally different level of scale and impact. A central focus of this role is ensuring that Autodesk owns its intelligence. As AI capabilities become embedded across every major enterprise software platform, the risk of institutional knowledge migrating into vendor systems — and being sold back at a premium — is real and growing. This leader will define and execute the architecture that keeps Autodesk's AI on Autodesk's terms: built on open data foundations the company controls, governed by standards the company sets, and compounding in value inside Autodesk's walls.

Requirements

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. This is a data engineer at their core who has evolved into AI.
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
Experience 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
Proven track record 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. This is the core discipline the role is built on.
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
Demonstrated ability to lead globally distributed, multi-disciplinary teams across time zones and functions — with empathy for the people and accountability for the outcomes
A track record of building organizational cultures where engineers want to work: where judgment is trusted, ambition is expected, and delivery is celebrated
Comfort with ambiguity — this leader creates clarity for others, not the other way around

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
Establish portfolio governance: a consistent, transparent framework for evaluating, prioritizing, and sequencing AI initiatives based on business value, data readiness, strategic fit, and resource availability
Drive build vs. buy vs. partner decisions with discipline — leveraging vendor AI capabilities where appropriate while protecting investment in Autodesk-owned, differentiated intelligence
Establish 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
Partner with Autodesk's Trust organization to adopt, adapt, and extend the enterprise AI governance framework — applying existing standards for model risk, bias evaluation, privacy-by-design, and ethical AI to AIDA's programs and accelerating their maturation
Ensure AI initiatives operate in compliance with the evolving global regulatory landscape — EU AI Act, GDPR, CCPA, and emerging obligations — working in close coordination with Legal and Trust teams
Extend and enforce policies governing what data can interact with which AI systems, including third-party and vendor AI tools, building on the Trust team's existing framework at the architecture level
Provide regular reporting to the CIO and executive leadership on AI portfolio health, governance posture, risk exposure, and business value realization
Lead, develop, and inspire a globally distributed team of data engineers, AI/ML practitioners, product managers, and program leaders — and shape the organizational structure and operating model that best executes the strategy
Assess and evolve the team architecture as needed and build new capabilities in whatever configuration drives the best outcomes
Recruit to close genuine capability gaps in AI architecture, ML engineering, and AI governance, while retaining and elevating the talent already delivering results
Serve as the CIO's primary AI thought partner and trusted advisor to executive leaders across Autodesk on technology strategy, AI investment, and the future of human and digital work
Foster a culture where engineering judgment is respected, ambition is rewarded, and the team is empowered to build things that matter