Salary
💰 $240,000 - $325,000 per year
Tech Stack
AWSAzureCloudGoogle Cloud Platform
About the role
- Lead enterprise-wide adoption of AI agents and define vendor partner ecosystem strategies
- Develop and execute a comprehensive Agentic AI strategy aligned with business objectives
- Drive full lifecycle of AI products from research to production deployment and build scalable infrastructure and deployment pipelines
- Partner with product, engineering, and business teams to identify high-impact AI opportunities and integrate agents into workflows and customer channels
- Establish best practices for model development, evaluation, monitoring, governance, and operational readiness
- Build assessment frameworks for agent adoption including utility, ROI, and risk evaluation
- Manage vendor relationships and ensure partner solutions align with enterprise architecture, technology, and compliance standards
- Drive change leadership, awareness, education, playbooks, and enterprise adoption of agentic AI solutions
Requirements
- 10+ years of progressive leadership in technology, AI/ML, and/or cloud-enabled transformation
- Solid foundation in cloud architectures (AWS, Azure, GCP), AI/ML platforms, and modern application ecosystems
- Experience in operational excellence, scaling enterprise technology, and embedding governance and risk management
- Experience evaluating, adopting, and scaling emerging AI capabilities in large, complex organizations
- Deep understanding of AI agents, LLMs, orchestration frameworks, and monitoring/ops
- Experience driving cross-business value creation through AI technology adoption
- Exceptional executive presence, communication, and relationship-building with technical and business stakeholders (preferred)
- Demonstrated ability to lead through influence across a matrix organization (preferred)
- Forward-leaning mindset toward innovation with pragmatic ability to deliver measurable outcomes (preferred)
- Related skills: Business Acumen, Data Preprocessing, Data Science, Innovation, Machine Learning, Market/Industry Dynamics, Predictive Modeling, Programming, Statistics