Define AI Roadmap: Craft a comprehensive enterprise-wide AI strategy and vision that aligns with the company's long-term objectives.
Identify Opportunities: Partner with C-level executives to identify high-impact use cases where AI can solve business problems or create new revenue streams.
Business Alignment: Ensure all AI initiatives deliver measurable value, defining key performance indicators (KPIs) to track success.
Team Management & Development
Build High-Performing Teams: Recruit and manage cross-functional teams, including data scientists, machine learning engineers, and researchers.
Mentorship: Provide technical leadership and professional guidance to team members, fostering a culture of continuous learning and innovation.
Cross-Functional Collaboration: Coordinate with IT, product, and engineering teams to integrate AI solutions into existing workflows and products.
Technical Oversight & Innovation
Oversee Development: Lead the design, prototyping, and deployment of advanced AI/ML models (e.g., NLP, Generative AI, Computer Vision).
Technology Selection: Evaluate and select appropriate AI platforms, vendors, and large language models (LLMs) for organizational use.
Standardization: Establish MLOps standards, model lifecycle practices, and quality assurance processes for production environments.
Governance, Ethics & Risk Management
Ethical AI: Oversee the design of policies for safe and responsible AI use, addressing issues like bias, fairness, and transparency.
Regulatory Compliance: Ensure all AI activities adhere to data protection regulations (e.g., GDPR, CCPA) and industry-specific standards.
Risk Mitigation: Manage the legal, operational, and security risks associated with deploying AI at scale.
Advocacy & External Representation
Thought Leadership: Act as the company's ambassador in the AI community and represent the organization at industry conferences.
Literacy Programs: Drive "AI literacy" across the organization, educating non-technical stakeholders on the capabilities and limitations of AI.
Partnership Management: Build strategic partnerships with academic institutions, research organizations, and technology vendors.
Requirements
Bachelor's degree holder
At least 20 years of solid experience gained from large companies with a strong focus on AI and data
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