We are seeking a Senior AI Architect/ AI Practice Leader to define and lead the enterprise AI practice, ensuring AI initiatives deliver measurable business value, are responsibly governed, and are widely adopted across the organization.
This role owns AI strategy, architecture, monetization, governance, and adoption, acting as the principal authority and spokesperson for AI initiatives.
Key Responsibilities
- Define AI vision, roadmap, operating model, and architectural standards.
- Lead and grow a multidisciplinary AI team; ensure delivery excellence.
- Identify high-impact AI opportunities aligned to business priorities.
AI Monetization & Business Alignment
- Own AI business intake and monetization processes.
- Assess initiatives for commercial viability, risk, ethics, and strategic fit.
- Track AI systems in development/production and realized business outcomes.
Architecture, Delivery & Lifecycle Oversight
- Act as Chief AI Architect across GenAI, LLMs, NLP, CV, RAG, and MLOps.
- Ensure scalable, secure, and production-ready AI deployments.
- Implement lifecycle governance, performance monitoring, and incident handling.
Adoption, Change & Governance
- Drive AI adoption KPIs through training, enablement, and change management.
- Embed responsible AI, transparency, auditability, and compliance practices.
- Maintain enterprise standards, documentation, and governance checkpoints.
Stakeholder & Thought Leadership
- Partner with business leaders, clients, and technology partners.
- Represent the organization as an AI thought leader externally.
- Communicate AI progress, value, and direction across the enterprise.
Qualifications
- Bachelor's or Master's degree in Computer Science, AI, Data Science, or related fields.
- Deep expertise in AI/ML, Generative AI, LLMs, and modern AI architectures.
- Strong business acumen with experience in AI value realization.
- Excellent executive communication and cross-functional leadership skills.
Added Advantages
- Experience in Supply Chain, Logistics, Manufacturing, or Enterprise Systems.
- Familiarity enterprise IT governance.
- Experience building or scaling an AI Center of Excellence (CoE) or AI practice.
- Publications, patents, open-source contributions, or recognized AI thought leadership.