Skew Talent · 18 hours ago
Head of AI Infrastructure Engineering
United States
Full-time
Remote
Director/ExecutiveSkew Talent is seeking a Head of AI Infrastructure Engineering to oversee the development of a large-scale AI infrastructure deployment in India. The role involves designing GPU cluster architectures, managing vendor relationships, and leading a team of engineers to ensure optimal performance and reliability of the infrastructure.
Staffing & Recruiting
Hiring Manager
Kathleen Walsh
Responsibilities
Design GPU cluster architectures for training and inference at scale (thousands of GPUs, not dozens)
Specify hardware configurations: GPU servers, networking fabric, storage systems, power and cooling
Evaluate and select vendors; negotiate technical specifications with OEMs like Dell, Supermicro, HPE, and NVIDIA directly
Work with facility teams on power infrastructure, electrical distribution, and cooling solutions for high-density AI deployments
Build automation for cluster provisioning, configuration management, and lifecycle operations
Implement job scheduling and workload management (Slurm, Kubernetes, custom orchestration as needed)
Establish monitoring, alerting, and observability for infrastructure health at scale
Lead calls with overseas teams to review progress, present architectures, and provide technical guidance
Define operational runbooks, incident response, and SRE practices
Build and lead a team of infrastructure engineers, systems administrators, and hardware specialists
Travel to India periodically to work directly with data center and operations teams
Qualification
Required
You've built GPU infrastructure at scale; you know NVIDIA's ecosystem (DGX, HGX, NVLink, NVSwitch, CUDA, NCCL) from hands-on experience, not just vendor briefings
Deep expertise in high-performance networking: InfiniBand, 400G Ethernet, RDMA, GPUDirect; you understand why network topology matters for distributed training
Strong Linux systems engineering background; you've managed thousands of nodes and know what breaks at scale
Experience with storage systems for ML workloads: Lustre, GPFS, BeeGFS, NVMe-oF, parallel file systems
You've worked at a hyperscaler (AWS, GCP, Azure) or AI-native infrastructure provider (CoreWeave, Lambda, Crusoe, or similar); you know what good looks like
Comfortable with data center operations: power, cooling, rack density, PUE optimization; you can have a real conversation with facilities engineers
You can make decisions with incomplete information and defend them technically; you don't wait for perfect specs before moving forward
Able to hold a high bar and push teams toward excellence without being a know-it-all
Strong communicator who can translate between hardware vendors, operations teams, and business stakeholders across time zones
Hungry to build something from the ground up; you're not looking for a role where you inherit someone else's architecture
Comfortable with ambiguity and an ability to take confident action when there are missing details
Preferred
Experience with advanced cooling: liquid cooling, two-phase cooling, immersion systems
Background in greenfield data center buildouts, not just operating existing infrastructure
Familiarity with India-specific considerations: power procurement, regulatory requirements, vendor landscape
Prior work with AI/ML frameworks and MLOps; you understand what the workloads actually look like
Benefits
Medical and Dental benefits
401K
Office space in Seattle with remote flexibility; we value quality candidates over location
Direct reporting to leadership with minimal bureaucracy
Ground-floor opportunity to build infrastructure at unprecedented scale
Small, sharp team culture that uses AI extensively in our own work
Company
Skew Talent
Honest, straightforward recruiting & talent strategy.
0-1 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase