Type: Contract (12 Months)
Payment Terms: 30 days after invoice
Shift: PST Time Zone
Laptop/MacBook: To be managed by vendor
Joining Date: Immediate

Qualifications

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

• 15+ years of experience in infrastructure architecture.

• 3–5 years of dedicated experience in AI-specific infrastructure design and implementation.

• Proven track record of deploying scalable and secure AI solutions in cloud environments.

Key Responsibilities

• Architect the Future: Lead end-to-end design and development of AI infrastructure across hardware, software, networking, and multi-cloud environments.

• Innovate and Evaluate: Assess, select, and implement best-in-class tools & frameworks (TensorFlow, PyTorch, Kubernetes, Docker).

• Optimize for Performance: Build infrastructure that scales seamlessly with evolving AI/ML workloads, optimizing for cost and performance.

• Champion Security & Compliance: Define standards ensuring compliance with security policies, data protection regulations, and ethical AI principles.

• Data Pipelines: Collaborate on efficient data pipelines from ingestion to processing for AI model training and deployment.

• Lead & Inspire: Provide technical leadership and mentorship, fostering best practices in AI infrastructure.

• Problem-Solving: Diagnose and resolve complex infrastructure issues, ensuring high availability & reliability.

• Stay Ahead: Track the latest in AI, ML, LLMs, and cloud computing to drive innovation.

• Documentation: Maintain detailed documentation for infrastructure designs and operational procedures.

Technical Skills

• Strong command line expertise; experience with cloud-native and on-premise deployments.

• Deep understanding of deep learning architectures and Large Language Models (LLMs).

• Hands-on expertise in NVIDIA hardware/software, GPU performance tuning, and benchmarking.

• Proficiency in Python for infrastructure and AI-related tasks.

• Expertise in cloud service models (IaaS, PaaS, SaaS) and cloud-native architectures.

• Strong knowledge of networking, storage, and cloud security best practices.

• Hands-on with Infrastructure as Code (IaC) – Terraform, CloudFormation.

• Familiarity with DevOps/MLOps principles and automation practices.

• Strong problem-solving, analytical mindset, and data-driven approach.

• Excellent communication skills for client and stakeholder engagement.

• Proven leadership & mentoring experience in cross-functional teams.

Industry Background

• IT / Technology Services

Selection Process

• Online Interview