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.
Requirements
- 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.