AI Lab Infrastructure Engineer

Summary

Berkeley Research Group's AI Department is seeking an AI Infrastructure Engineer to lead the development of their Virtual AI Lab initiative. The role involves architecting and building a virtual access layer for the physical AI Lab, focusing on secure and scalable remote processing capabilities for large-scale document processing.

Responsibilities

• Design and implement a virtual access layer for the physical Ai Lab infrastructure
• Build scalable remote processing capabilities supporting 100,000+ documents per day
• Create customizable, expandable interfaces for different BRG business units
• Optimize infrastructure for maximum LLM token throughput (OpenAI/Anthropic)
• Implement secure authentication and access management systems
• Ensure high availability and fault tolerance for mission-critical AI workloads
• Lead infrastructure projects from conception to production deployment

Skills

• Prefer someone with four to eight (4-8) years of hands-on experience designing, deploying, and managing scalable cloud infrastructure
• Strong experience with Infrastructure as Code (IaC) tools and methodologies
• Experience designing, implementing, and maintaining scalable, secure, and cost-efficient cloud/on-prem solutions
• Proven ability to manage and lead projects to deliver high-quality, replicable solutions
• Proficiency in VCS (Git/GitHub), modern coding languages (Python, .NET, Java, etc.), Software Development Life Cycle, and CI/CD practices
• Experience with API design and implementation for distributed systems
• Knowledge of GPU infrastructure and optimization for AI workloads
• Hands-on experience with AWS Services including: EC2/Lambda (apps/functions), SageMaker (ML), S3 (file management), Fargate/ECS/EKS (containerization), CDK/Terraform (IaC), Cost Explorer/Budgets
• Experience with LLM deployment and optimization (OpenAI, Anthropic, etc.)
• Background in building AI/ML infrastructure and platforms
• Experience with virtual desktop infrastructure (VDI) or remote access solutions
• Knowledge of distributed computing and job scheduling systems
• AWS certifications (Solutions Architect, Machine Learning, or similar)
• Experience with cost management and optimization strategies in the cloud
• Familiarity with security best practices for AI systems and data handling

Qualifications

Must Haves

• Bachelor's degree in Computer Science, Information Technology, or a related field
• Prefer someone with four to eight (4-8) years of hands-on experience designing, deploying, and managing scalable cloud infrastructure
• Strong experience with Infrastructure as Code (IaC) tools and methodologies
• Experience designing, implementing, and maintaining scalable, secure, and cost-efficient cloud/on-prem solutions
• Proven ability to manage and lead projects to deliver high-quality, replicable solutions
• Proficiency in VCS (Git/GitHub), modern coding languages (Python, .NET, Java, etc.), Software Development Life Cycle, and CI/CD practices
• Experience with API design and implementation for distributed systems
• Knowledge of GPU infrastructure and optimization for AI workloads
• Hands-on experience with AWS Services including: EC2/Lambda (apps/functions), SageMaker (ML), S3 (file management), Fargate/ECS/EKS (containerization), CDK/Terraform (IaC), Cost Explorer/Budgets

Nice to Haves

• Experience with LLM deployment and optimization (OpenAI, Anthropic, etc.)
• Background in building AI/ML infrastructure and platforms
• Experience with virtual desktop infrastructure (VDI) or remote access solutions
• Knowledge of distributed computing and job scheduling systems
• AWS certifications (Solutions Architect, Machine Learning, or similar)
• Experience with cost management and optimization strategies in the cloud
• Familiarity with security best practices for AI systems and data handling