Assistant Vice President of Artificial Intelligence Job New York New York USA,IT/Tech

Location: New York

Overview

Under direction of the Vice President/Chief Data and Artificial Intelligence Officer, implements Artificial Intelligence (AI) to enhance high-quality care, optimize workflows, and ensure equity in healthcare delivery. Manages engineering teams, sets technical direction, and works collaboratively with cross-functional partners to translate AI research into real-world, production-grade AI solutions that deliver measurable improvements in patient care, financial and/or operational efficiency.

Essential Duties and Responsibilities

Leads AI engineers, data scientists, and Machine Learning professionals, ensuring technical excellence and consistent delivery of scalable AI solutions.

Defines and executes AI engineering roadmaps in partnership with senior leadership and aligns them with organizational goals.

Oversees the full lifecycle of AI/ML systems — from design and prototyping to deployment, monitoring, and related work.

Guides architecture decisions for AI platforms, data pipelines and model serving infrastructure; evaluates and integrates new AI tools and frameworks as needed.

Establishes and maintains best practices for model development, code quality, version control, model lifecycle management, and Machine Learning.

Develops and maintains collaborations with academic institutions, research organizations, and industry partners to advance AI capabilities.

May contribute to peer-reviewed publications presents at conferences, and stays engaged with the AI research community to keep the System at the forefront of innovation.

Collaborates with product, data, and infrastructure teams to align AI capabilities with enterprise needs; acts as a trusted technical advisor to the System’s stakeholders and non-technical partners.

Assignment Qualification Requirements

Master's degree from an accredited college or university in Computer Science, Engineering, or related discipline; and eight (8) years of experience in software/AI engineering, four (4) years of which must have been in a leadership role managing cross-functional technical teams such as AI/ML engineers, data scientists, and Machine Learning professionals, and with a proven track records of delivering enterprise-grade AI solutions;

or

A satisfactorily equivalent combination of education, training, and experience. However, all candidates must have a minimum of a Bachelor’s Degree in disciplines listed in “1” above, or in a related discipline, and preference will be given to applicants with a doctorate degree

Preferred Certifications

Google Cloud Professional Machine Learning Engineer.
Tensor Flow Developer Certificate.
Databricks Certified Professional Data Engineer

Preferred Knowledge Areas, Skills, Abilities, and other Qualifications

Proven expertise in machine learning, deep learning, generative AI, and AI system design and deployment.

Proficient in Python, Tensor Flow/PyTorch, cloud services (AWS, Azure, GCP), and MLOps tools.

Strong knowledge of Machine Learning practices, including model versioning, CI/CD for Machine Learning, and production monitoring.

Experience deploying large-scale AI systems in production environments.

Data Engineering & Big Data: SQL and No

SQL databases (e.g., Postgre

SQL, Mongo

DB), Apache Spark, Databricks, Airflow.

Version Control &

Collaboration:

Git, Git Hub, Git Lab, JIRA, Confluence.

APIs & Integration:
FastAPI, Flask, and tools for secure model deployment and EHR system integration (where applicable).

Proven track record of academic engagement, including collaborations, publications, or conference presentations in AI/ML fields.

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