VP AI Engineering - Enterprise

About the role

Sedgwick is hiring a Vice President, Generative (Gen) AI Engineering Enterprise, a remote position based in the U.S. The role provides executive leadership, strategy and accountability for the enterprise data and AI engineering ecosystem behind advanced analytics, data science and generative AI initiatives. It sets the vision, governance and execution model for the data supply chain powering machine learning platforms, feature stores and production-grade generative AI, and aligns investments to business outcomes, regulatory expectations and architectural sustainability across on-premise and multi-cloud environments.

Key responsibilities

• Define and lead the enterprise strategy for data and generative AI engineering, including standards, roadmaps and operating models.
• Oversight of enterprise ETL/ELT platforms that connect legacy on-premise systems (mainframe, SQL Server, DB2) with modern cloud data and AI platforms.
• Governance of feature stores, optimized datasets and AI-ready data products, and direction for vectorization, embeddings, RAG and secure data consumption.
• Own the enterprise Snowflake strategy, including architecture, performance, cost governance and integration with AWS and Azure AI services.
• Collaborate with Technology, Security, Infrastructure, Legal, Risk and Compliance to meet security, privacy and regulatory requirements.
• Set executive-level metrics and financial discipline, and guide engineering leaders and teams.
• Lead AI engineering for enterprise functions such as HR, Marketing, Finance and Legal, delivering LLM, agentic AI, workflow automation and knowledge-assistant use cases.
• Manage ChatGPT Enterprise and Claude, including access, licenses, connectors and integrations, and partner with Security, Privacy, Legal and AI Governance on access controls.
• Manage AI platform spend, licensing, chargeback/showback and vendor relationships with OpenAI, Anthropic and others.
• Lead a small engineering/platform team and establish operational dashboards for adoption, usage, cost, risk and value.

Required profile

• Bachelor's degree in Computer Science, Data Engineering, Artificial Intelligence or a related field; Master's degree preferred.
• 10+ years of engineering, platform or enterprise technology experience, with 5+ years in technical leadership.
• Experience building AI solutions for corporate functions such as HR, Marketing, Finance or Legal.
• Experience administering enterprise SaaS or AI platforms at significant scale, and establishing AI governance and access controls.
• Strong financial management skills, including technology spend, licenses, vendor spend and forecasts.

Required skills

• Hands-on understanding of LLMs, agentic AI, RAG, APIs and workflow automation.
• Modern data architectures, cloud data platforms and AI enablement, including Snowflake and AWS/Azure.
• Identity, SSO, RBAC, connectors, APIs and data permissions.
• Experience with ChatGPT Enterprise, Claude Enterprise, Microsoft Copilot or similar platforms strongly preferred.