AI Infrastructure Lead

Blue Signal Search; California; On-site; USD 180,000 - 280,000; Full time

Benefits offered by this job

Equity participation

Leadership exposure

Ownership of infrastructure

Job summary

Blue Signal Search is seeking an AI Infrastructure Lead for our client, an AI infrastructure innovator in California. You will own mission-critical GPU infrastructure and shape deployment of AI workloads at scale.

You will work with founders and engineering specialists, define standards, and drive reliability, performance, and security across high-density compute environments. Equity and leadership growth await in this early-stage venture.

Qualifications

• Proven experience implementing, commissioning, and managing production GPU clusters in demanding AI, cloud computing, or HPC environments.
• Strong understanding of AI inference infrastructure, distributed workload management, GPU resource allocation, and multi-tenant computing architectures.
• Advanced knowledge of InfiniBand, RoCE, and related infrastructure integration requirements.
• Familiar with high-density compute hardware, thermal management, power distribution, and advanced cooling solutions.
• Experience supporting externally facing compute services with reliability and scalability.
• Ability to coordinate complex hardware deployments with vendors, field technicians, and engineering teams.
• Familiarity with NVIDIA GPU reference architectures, liquid-cooled systems, microgrids, or DC power environments is advantageous.

Responsibilities

• Architect scalable GPU computing environments and standardized hardware configurations for enterprise AI inference workloads.
• Direct physical infrastructure deployments, equipment installation, system commissioning, hardware validation, and production readiness.
• Oversee GPU cluster performance, optimize availability, utilization, reliability, and resource efficiency.
• Develop and support inference-serving infrastructure for external customers, including workload orchestration and multi-tenant environments.
• Partner with energy and engineering teams to align compute with electrical capacity and cooling performance.
• Manage relationships with hardware manufacturers, networking providers, and integration partners.
• Establish repeatable deployment procedures and performance benchmarks for future expansion.

Skills

GPU clusters

AI inference infra

High-speed networking

High-density compute

External compute services

Hardware deployments

NVIDIA architectures

Job description

Our client, an emerging innovator in AI infrastructure, is seeking an AI Infrastructure Lead to help shape the next generation of high-performance computing environments. This is a rare opportunity to join a growing technology venture at an early stage, take ownership of mission-critical GPU infrastructure, and influence how advanced AI workloads are deployed and supported at scale. With direct access to company leadership, meaningful technical autonomy, and equity participation, this role offers the opportunity to turn ambitious infrastructure concepts into production-ready systems.

This Role Offers:

• Competitive base salary and equity participation, providing an opportunity to share in the company's long-term growth.
• Early-stage leadership opportunity with significant influence over technical architecture, infrastructure strategy, and operational standards.
• Exposure to advanced AI infrastructure, high-density computing, and innovative power and cooling technologies.
• Close collaboration with company founders, engineering specialists, and strategic technology partners.

Focus:

• Architect scalable GPU computing environments, developing standardized hardware configurations for enterprise-grade AI inference workloads.
• Direct physical infrastructure deployments, coordinating equipment installation, system commissioning, hardware validation, and production readiness.
• Oversee GPU cluster performance, implementing operational practices that optimize availability, utilization, reliability, and resource efficiency.
• Develop and support inference-serving infrastructure for external customers, including workload orchestration, resource scheduling, and secure multi-tenant environments.
• Partner with infrastructure and energy engineering teams to align compute requirements with electrical capacity, cooling performance, and system resilience.
• Manage technical relationships with hardware manufacturers, networking providers, and integration partners to ensure successful delivery and ongoing support.
• Establish repeatable deployment procedures, performance benchmarks, and operational frameworks that support future infrastructure expansion.

Skill Set:

• Proven experience implementing, commissioning, and managing production GPU clusters in demanding AI, cloud computing, or high-performance computing environments.
• Strong understanding of AI inference infrastructure, distributed workload management, GPU resource allocation, and multi-tenant computing architectures.
• Advanced knowledge of high-speed networking technologies, including InfiniBand, RoCE, and associated infrastructure integration requirements.
• Practical familiarity with high-density compute hardware, thermal management, power distribution, and advanced cooling solutions.
• Experience supporting externally facing compute services, with an emphasis on infrastructure reliability, customer performance, and operational scalability.
• Ability to coordinate complex hardware deployments involving equipment vendors, field technicians, engineering teams, and third-party service providers.
• Familiarity with NVIDIA GPU reference architectures, liquid-cooled systems, battery-backed infrastructure, microgrids, or DC power environments is advantageous.