Principal – Architecture

Experience:

Location:

Type:

What You’ll Do

• Architect the Future: Lead the end-to-end design and development of AI infrastructure, including hardware, software, networking, and multi-cloud environments.
• Innovate and Evaluate: Assess, select, and implement best-in-class technologies, tools, and frameworks (e.g., TensorFlow, PyTorch, Kubernetes, Docker) to build and maintain AI platforms.
• Optimize for Performance: Engineer and implement infrastructure that scales seamlessly with evolving AI/ML needs, continuously monitoring and optimizing for performance and cost-efficiency.
• Champion Security and Compliance: Define and enforce infrastructure standards and best practices, ensuring compliance with security policies, data protection regulations, and ethical AI principles.
• Build Data-Driven Pipelines: Collaborate on the architecture and implementation of efficient data pipelines for AI models — from ingestion and storage to processing and management.
• Lead and Inspire: Provide technical leadership and mentorship to cross-functional teams, fostering a culture of excellence and best practices in AI infrastructure.
• Solve Complex Challenges: Diagnose and resolve intricate infrastructure issues to ensure high availability and reliability of AI systems.
• Stay Ahead of the Curve: Keep updated on the latest advancements in AI, machine learning, and cloud computing to drive innovation.
• Document for Success: Create and maintain comprehensive documentation for AI infrastructure designs, implementations, and operational procedures.
  

What You’ll Bring

Education

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
  

Experience

• 15+ years of experience in infrastructure architecture.
• At least 3–5 years dedicated to designing and building AI-specific infrastructure.
• Proven success in deploying scalable and secure AI solutions in cloud environments.
• Extensive hands-on experience with containerization and orchestration (Docker, Kubernetes).
  

Technical Prowess

• Proficiency with command line and experience in both cloud-native and on-premise data center deployments.
• Strong understanding of deep learning architectures and Large Language Models (LLMs).
• Expertise in NVIDIA hardware/software including performance tuning and diagnostics.
• Hands-on experience with GPU systems: performance testing, tuning, and benchmarking.
• Proficiency in programming (Python preferred).
• Deep understanding of cloud service models (IaaS, PaaS, SaaS) and cloud-native architectures.
• In-depth networking, storage, and security best practices in cloud contexts.
• Experience with Infrastructure as Code (IaC) tools like Terraform or CloudFormation.
• Familiarity with DevOps and MLOps principles.
  

Soft Skills

• Exceptional problem-solving and analytical abilities with a data-driven approach.
• Excellent communication skills, able to explain complex concepts to diverse audiences.
• Proven leadership, mentoring, and collaboration abilities.
• Strategic thinking to align technical solutions with business goals.
• Proactive, adaptable, and a continuous learner in a fast-evolving tech landscape.
  

Skills

Mandatory Skills:

• HPUX Administration
• Kubernetes
• Nutanix
• Solaris 10 & 11 Administration
• Azure Infra Services
• VMware ESXi
• Windows Server
• VMware VxRail HCI Administration
• AWS Infra Services
• RedHat Linux Administration
• GCP Infra Services
• AIX Administration
• RedHat OpenShift
• Infrastructure Architecture
• Dell EMC VxRail