Sr Director, AI Strategy & Architecture
New
Based in the United StatesFull-TimeDirector
Salary not disclosed
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Job Details
- Experience
- 10–15 years
- Required Skills
- CybersecurityStakeholder managementChange ManagementPrompt EngineeringLLM
Requirements
- 10–15 years of experience in technology, engineering, architecture, or related roles with significant AI/ML implementation experience in recent years.
- Deep knowledge of modern AI technologies, including large language models (LLMs), agentic frameworks, vector databases, automation platforms, and AI development tools.
- Experience designing and deploying enterprise-scale AI solutions with strong understanding of architecture, integration, and operational considerations.
- Strong understanding of cybersecurity principles and ability to evaluate data protection, governance, and risk considerations in AI deployments.
- Proven ability to lead enterprise transformation initiatives through influence, collaboration, and stakeholder alignment.
- Exceptional executive communication skills with the ability to explain complex AI concepts to both technical and business audiences.
- Experience building business cases, measuring technology ROI, and communicating strategic value to senior leadership.
- Ability to operate effectively in global, multi-country environments with complex regulatory and compliance requirements.
- Experience with organizational change management, internal consulting, training, or capability-building initiatives.
Responsibilities
- Serve as the senior internal AI advisor, developing enterprise AI strategies and guiding teams in identifying, prioritizing, and implementing high-impact AI opportunities.
- Design and implement end-to-end AI workflows across departments including Engineering, Sales, Marketing, Finance, Legal, HR, Operations, and Customer Success.
- Build scalable AI architectures by connecting data platforms, AI models, automation tools, and internal applications into secure production-ready solutions.
- Translate business challenges into practical AI solutions, including LLM integrations, prompt engineering, workflow automation, intelligent data pipelines, and agent-based systems.
- Ensure AI initiatives follow security, governance, compliance, and responsible AI standards across global operations.
- Create AI enablement programs including workshops, executive briefings, playbooks, training materials, and reference guides to increase organizational AI maturity.
- Define success criteria for AI programs and communicate ROI, business impact, and recommendations to executive stakeholders.
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