Senior AI Architect

Role overview

As a Senior AI Architect Engineer, you will be instrumental in designing and orchestrating advanced AI solutions that integrate seamlessly into our business processes and technology ecosystem. Your role will focus on creating scalable, intelligent architectures that drive innovation, operational efficiency, and business transformation. By aligning AI strategy with organizational goals, you will ensure our AI initiatives are robust, adaptable, and positioned to meet future challenges, enabling a competitive advantage in an evolving market.

The role

To support our strategic growth and innovation agenda, we seek a seasoned a Senior AI Architect Engineer who can lead complex AI projects and foster cross-functional collaboration.

Expertise and experience

• Minimum of 5 years of experience in architecture, machine learning engineering, or data science, with a focus on delivering enterprise-grade AI solutions.
• Proven track record in designing, deploying, and operationalizing AI/ML models in production environments.
• Deep familiarity with AI/ML frameworks, and experience with cloud AI platforms like AWS SageMaker, Azure AI, or Google AI Platform.
• Strong expertise in data engineering, data modelling, and integration, with the ability to architect end-to-end AI pipelines.
• Proficiency in programming languages including Python, SQL, and experience with containerization (Docker) and orchestration (Kubernetes).
• Experience with MLOps practices including CI/CD pipelines, model monitoring, and automated retraining.
• Solid understanding of AI ethics, data privacy, and regulatory compliance.

Technical Leadership

• Lead the design and implementation of scalable AI architectures that solve complex business problems and integrate with existing systems.
• Define and enforce AI development standards, best practices, and governance frameworks across projects.
• Drive technology evaluation and selection to ensure the adoption of the most effective AI tools and platforms.
• Implement robust data security, privacy controls, and ethical AI guidelines within all AI initiatives.
• Ensure model accuracy, reliability, and maintainability through rigorous validation and continuous monitoring.
• Foster innovation by integrating emerging AI technologies and methodologies into business solutions.
• Mentor and guide cross-functional teams, promoting AI literacy and excellence.
• Architect and maintain cloud-native AI infrastructure to support scalability and agility.
• Champion automation and orchestration to streamline AI workflows and deployment processes.