AI Senior Program Manager

• Proven track record of leading projects that bridge software engineer, data scientist , legal compliance And executive stakeholders.
• Knowledge of Cloud computing knowledge (AWS, Google, Azure). Costs associated to GPU.
• Management of dependencies, budgets, long term strategic value across project.
• Manage multiple AI initiatives from use‑case identification through implementation and value realization.
• Establish an AI program roadmap, milestones, dependencies, risks, and governance.
• Coordinate business, AI engineering, architecture, data, security, legal, risk, and operations stakeholders.
• Establish a structured process for evaluating and prioritizing AI opportunities.
• Work with stakeholders to develop business cases and measurable success criteria.
• Track implementation cost, benefits, business outcomes, and AI ROI.
• Facilitate decisions on whether a use case should employ GenAI, traditional ML, automation, or conventional application development.
• Coordinate pilots and production implementations.
• Manage resource requirements, dependencies, budgets, risks, issues, and executive reporting.
• Establish repeatable program‑management practices for scaling AI adoption.
• Drive executive‑level steering committee discussions and decision‑making.
• Cross‑Functional
  
  Collaboration:
  
  Partner with data scientists, software developers, and product managers to align technical execution with business outcomes.
• Technology Evaluation:
  Select optimal frameworks, vector databases, cloud services (AWS, Azure, GCP), and hardware resources for specific workloads.

• Proven track record of leading projects that bridge software engineer, data scientist , legal compliance And executive stakeholders.
• Knowledge of Cloud computing knowledge (AWS, Google, Azure). Costs associated to GPU.
• Management of dependencies, budgets, long term strategic value across project.

• Manage multiple AI initiatives from use‑case identification through implementation and value realization.
• Establish an AI program roadmap, milestones, dependencies, risks, and governance.
• Coordinate business, AI engineering, architecture, data, security, legal, risk, and operations stakeholders.
• Establish a structured process for evaluating and prioritizing AI opportunities.
• Work with stakeholders to develop business cases and measurable success criteria.
• Track implementation cost, benefits, business outcomes, and AI ROI.
• Facilitate decisions on whether a use case should employ GenAI, traditional ML, automation, or conventional application development.
• Coordinate pilots and production implementations.
• Manage resource requirements, dependencies, budgets, risks, issues, and executive reporting.
• Establish repeatable program‑management practices for scaling AI adoption.
• Drive executive‑level steering committee discussions and decision‑making.
• Cross‑Functional
  
  Collaboration:
  
  Partner with data scientists, software developers, and product managers to align technical execution with business outcomes.
• Technology Evaluation:
  Select optimal frameworks, vector databases, cloud services (AWS, Azure, GCP), and hardware resources for specific workloads.

• Discretionary Annual Incentive.
• Comprehensive Medical Coverage:
  Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
• Family Support:
  Maternal & Parental Leaves.
• Insurance Options:
  Auto & Home Insurance, Identity Theft Protection.
• Convenience & Professional Growth:
  Commuter Benefits & Certification & Training Reimbursement.
• Time Off:
  Vacation, Time Off, Sick Leave & Holidays.
• Legal & Financial Assistance:
  Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

Salary Range $100,000 - $120,000 a year

BACHELOR OF COMPUTER SCIENCE