AI Infrastructure Architect

Job summary

The AI Infrastructure Architect role is centered on designing and optimizing AI and machine learning infrastructure for real-world applications. Responsibilities include architecting compute resources, deploying AI systems, and leading container orchestration with tools like Docker and Kubernetes, while ensuring performance, cost, and scalability. The position also involves mentoring junior engineers and contributing to architectural decisions.

Qualifications

• Practical experience in coding, building, monitoring, troubleshooting applications of AI/ML models
• Strong understanding of AI and machine learning
• Strong understanding of computing infrastructure
• Proficiency in programming languages such as Python, Java, or C++
• Experience with data pipeline and workflow management tools
• Strong problem-solving skills and ability to work in a fast-paced environment
• Excellent communication and collaboration skills
• Proven experience in AI/ML infrastructure engineering or related roles

Responsibilities

• Write, review, and debug code, scripts, 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, power, cost, and scalability
• Evaluate and select tools, frameworks, and platforms
• Integrate AI models and systems into existing enterprise systems
• Own AI monitoring and infrastructure health across InfraOps and MLOps
• Independently troubleshoot and resolve complex issues across the computational stack
• Mentor junior engineers and lead code reviews
• Define and document architecture standards, processes, and procedures

Skills

Degrees

Relocation