Lead AI/ML Engineering

S R INTERNATIONAL INC • Phoenix, AZ

1d • Hybrid

About The Position

The State of Arizona’s Arizona Department of Economic Security is seeking an experienced AI/ML Engineering & Governance Manager to lead artificial intelligence initiatives from strategic planning through scalable and responsible deployment. The role oversees AI engineers, Business Analysts, and operations specialists, translating business objectives into technical requirements and managing AI/ML model lifecycles. The position ensures AI solutions deliver measurable business value while meeting ethical, regulatory, and data privacy requirements. The role is based in Phoenix, Arizona, with a hybrid work arrangement and flexible work-from-home options. The contract is long-term, with work scheduled Monday through Friday, 8:00 AM to 5:00 PM, for 40 hours per week.

Requirements

• At least 5 years of experience in Data Science, Machine Learning, or AI Engineering.
• At least 2 years of experience leading and managing AI teams.
• Experience with AI/ML architectures and machine learning lifecycles (MLOps).
• Governance and compliance experience, including risk assessments, model validation, bias testing, and data privacy compliance.
• Microsoft OpenAI experience.
• Strong project management and stakeholder communication skills.
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Statistics, or a related technical field.

Nice To Haves

• OpenAI experience.
• Experience with modern AI/ML frameworks such as PyTorch, TensorFlow, and LangChain.
• Experience with cloud AI services across Azure, AWS, or GCP.

Responsibilities

• Define roadmaps, scope, and objectives for enterprise AI and machine learning initiatives.
• Bridge technical teams, including data science, MLOps, and software engineering, with business stakeholders.
• Hire, mentor, and manage AI/ML specialists, providing coaching, performance management, and career development.
• Oversee AI model deployment, monitoring, data drift tracking, and retirement.
• Coordinate risk assessments, model validation, bias testing, and data privacy compliance.
• Track latency, model availability, accuracy, and business return on investment.
• Deliver complex technical projects on time and within budget using Agile or traditional project management methodologies.
• Explain complex AI and algorithmic concepts to executive leadership, product teams, and clients.

What This Job Offers

• Career Level: Manager