Chief AI Architect

About The Role

We’re looking for a Chief AI Architect to lead the organization’s overall AI vision, strategy, and execution, ensuring alignment with business objectives and long-term growth goals.

You’ll act as the principal architect and implementer of AI solutions — from design and prototyping to large-scale deployment across business functions.

This is a senior, high-impact role for someone who combines deep technical acumen with strategic leadership and hands-on delivery.

What You'll Do

• Collaborate with executive leadership to identify high-impact AI opportunities that drive operational efficiency, innovation, and revenue growth.
• Build and lead a cross-functional AI Center of Excellence, bringing together data scientists, engineers, and domain experts to deliver enterprise-grade AI solutions.
• Champion the use of Generative AI, Machine Learning, NLP, and advanced analytics to enhance products, services, and internal processes.
• Oversee the development and governance of data infrastructure, ensuring data quality, accessibility, and compliance with privacy and security standards.
• Establish and enforce AI ethics, risk management, and responsible AI practices within the organization.
• Develop strategic partnerships with technology providers, academic institutions, and research organizations to accelerate AI innovation.
• Serve as a technical advisor to leadership, translating complex AI concepts into actionable insights and business value.
• Stay ahead of emerging technologies and lead hands-on experimentation, prototyping, and technical evaluations of new AI tools and models.

• 15+ years of experience in Digital Technology, with at least 4 years in AI/ML leadership roles across implementation, research, or product environments.
• Proven track record of end-to-end delivery of AI systems, from conceptualization to production — including model development, MLOps, and integration.
• Demonstrated experience translating AI strategy into business impact, with measurable ROI and operational outcomes.
• Deep technical expertise in machine learning, deep learning frameworks (TensorFlow, PyTorch), large language models, and cloud AI platforms.
• Strong background in data engineering, including data pipelines, architecture, and governance frameworks.
• Strong software engineering background, capable of guiding teams through architectural decisions, code reviews, and deployment processes.
• Excellent understanding of AI ethics, data privacy, and regulatory frameworks (GDPR, Responsible AI guidelines, etc.).
• Exceptional leadership and communication skills — able to engage with both technical teams and non-technical executives.
• Entrepreneurial mindset with the ability to innovate, experiment, and deliver in fast-moving environments.