AI Infrastructure Architect (All Genders)

Job summary

Hands-on role designing and optimizing AI and machine learning infrastructure, coding, deploying AI systems, and mentoring junior engineers.

Qualifications

• Practical experience in coding and troubleshooting AI/ML applications.
• Strong understanding of AI and machine learning.
• Knowledge of computing infrastructure, preferably AI infrastructure.
• Proficiency in programming languages such as Python, Java, or C++.
• Experience with data pipeline and workflow management tools.
• Strong problem-solving skills.
• Excellent communication and collaboration skills.
• Experience in AI/ML infrastructure engineering on hyperscaler platforms.

Responsibilities

• Write, review, and debug code and infrastructure-as-code for AI infrastructure.
• Architect, configure, and provision compute resources across cloud and on-premises environments.
• Design and maintain deployment automation and CI/CD pipelines.
• Deploy AI systems, models, and data pipelines into production.
• Lead container orchestration and model serving using Docker and Kubernetes.
• Architect and optimize the computational stack for performance and scalability.
• Evaluate and select tools and frameworks for infrastructure.
• Integrate AI models into existing enterprise systems.
• Own AI monitoring and infrastructure health across InfraOps and MLOps.
• Independently troubleshoot and resolve complex issues across the stack.
• Mentor junior engineers and lead code reviews.
• Define and document architecture standards and best practices.

Skills

Degrees

Relocation