AI Governance Engineer

Tampa General Hospital5 months ago
Tampa, FL, United States
Hybrid
Full-time
Junior Level (1-3 years)

Job Description

Position Overview

The AI Governance Engineer ensures the safe, effective, and ethical deployment of AI/ML across the FHSC system. In this role, the engineer operationalizes the governance framework for the full AI lifecycle, conducts technical due diligence of internal and external AI systems, and establishes robust post-implementation monitoring and auditing to safeguard patient care, regulatory compliance, and institutional integrity. The engineer collaborates with clinical leaders, data scientists, IT, Legal, Compliance, Safety/Risk, and Procurement to embed responsible AI practices in both vendor and in-house solutions.

Primary Location: Tampa

Work Location:

TGH Corporate Center, 606 W Kennedy Blvd, Tampa 33606

Eligible for Remote Work:

Hybrid Remote

Shift Hours:

8:00 am - 5:00 pm

Job Type:

Hybrid Remote

Key Responsibilities

  • Ensure the safe, effective, and ethical deployment of AI/ML across the FHSC system.
  • Operationalize the governance framework for the full AI lifecycle.
  • Conduct technical due diligence of internal and external AI systems.
  • Establish robust post-implementation monitoring and auditing.
  • Collaborate with diverse teams to embed responsible AI practices.

Required Qualifications

  • Bachelor’s Degree in Computer Science, Data Science, Engineering, or a related field.
  • Required Certifications: CRISC, CIPT, CISA, CAIGP, AIGP, CAIGS, and/or CAIG&CS.
  • 3–6 years of experience in AI/ML model validation, technical risk management, or governance in a regulated environment.
  • Professional certification in risk, privacy, audit, or AI governance is required.

Benefits & Perks

  • Compensation: Minimum Salary $140,878.00
  • Full-time schedule (Monday to Friday)
  • Day shift: 8:00 am - 5:00 pm

Required Skills

technical risk management
technical due diligence
stakeholder collaboration
regulatory compliance
governance framework implementation
AI/ML model validation
post-implementation monitoring
risk assessment