Remote VP of AI Engineering, Enterprise

Sedgwick; Orlando (FL); Remote; USD 350,000 - 700,000; Full time

Job summary

Sedgwick is seeking a VP AI Engineering - Enterprise to lead the data and AI engineering ecosystem, aligning investments with business outcomes across on‑premise and multi‑cloud environments. You will govern platforms enabling ML, feature stores, and production-grade generative AI capabilities.

You will drive architectural strategy, governance, and executive collaboration with Security, Legal, and Compliance to ensure value, risk management, and scalable delivery.

Qualifications

• Bachelor’s degree in Computer Science, Data Engineering, Artificial Intelligence or a related field.
• Masters Degree preferred.
• Ten years of engineering/analytics leadership experience with enterprise-scale data/AI initiatives.

Responsibilities

• Define enterprise strategy for data and generative AI engineering with standards and roadmaps.
• Oversee design and operation of ETL/ELT platforms integrating legacy systems with cloud data/AI platforms.
• Establish governance for feature stores and AI-ready data products for reproducibility and compliance.
• Lead enterprise AI enablement including vectorization, embeddings, and RAG approaches.
• Own Snowflake strategy and cloud integration across AWS/Azure.
• Provide executive guidance to ensure security, privacy, and regulatory alignment.

Skills

Executive leadership

LLMs knowledge

AI governance

Cloud data platforms

Education

Bachelor’s degree in CS/AI/Data Eng

Master’s degree preferred

Tools

Snowflake

AWS

Azure

Job description

Sedgwick is seeking a VP AI Engineering - Enterprise to lead the data and AI engineering ecosystem, aligning investments with business outcomes across on‑premise and multi‑cloud environments. You will govern platforms enabling ML, feature stores, and production-grade generative AI capabilities.

You will drive architectural strategy, governance, and executive collaboration with Security, Legal, and Compliance to ensure value, risk management, and scalable delivery.