Chief AI Architect
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About The Role
We’re looking for a Chief AI Architect to lead a project with an 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.
• Establish robust MLOps practices and CI/CD pipelines to ensure reliable, scalable, and observable AI systems in production.
• Lead enterprise-wide AI risk assessments, including model bias audits, explainability standards, and compliance reporting for regulators or clients.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.
• Experience architecting and deploying Generative AI / LLM solutions (e.g., RAG systems, fine-tuned models, agentic workflows) at enterprise scale.
• Hands-on experience with major cloud AI ecosystems (AWS Sage Maker, Azure AI, Google Vertex AI) and familiarity with multi-cloud or hybrid deployment strategies.
• Track record of building and mentoring high-performing, cross-disciplinary AI teams in matrixed or fast-scaling organizations.
• Familiarity with AI procurement and vendor evaluation — ability to assess build vs. buy decisions, negotiate with technology partners, and manage vendor SLAs.
• Comfort operating in ambiguity — proven ability to set structure, prioritize competing opportunities, and deliver results without a fully-defined playbook.
Requirements
- •15+ years of experience in Digital Technology, with at least 4 years in AI/ML leadership roles
- •Proven track record of end-to-end delivery of AI systems
- •Demonstrated experience translating AI strategy into business impact
- •Deep technical expertise in machine learning, deep learning frameworks, large language models, and cloud AI platforms
- •Strong background in data engineering
- •Strong software engineering background
- •Excellent understanding of AI ethics, data privacy, and regulatory frameworks
- •Exceptional leadership and communication skills
Nice to Have
- •Establish robust MLOps practices and CI/CD pipelines
- •Lead enterprise-wide AI risk assessments
- •Entrepreneurial mindset
Responsibilities
- •Identify high-impact AI opportunities
- •Build and lead a cross-functional AI Center of Excellence
- •Champion the use of Generative AI, Machine Learning, NLP, and advanced analytics
- •Oversee the development and governance of data infrastructure
- •Establish and enforce AI ethics, risk management, and responsible AI practices
- •Develop strategic partnerships with technology providers and academic institutions
- •Serve as a technical advisor to leadership
- •Lead hands-on experimentation, prototyping, and technical evaluations of new AI tools and models
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