About Us

Gimlet is building the first multi-silicon neocloud designed for fast, efficient inference.

As AI workloads become more complex and new hardware architectures emerge, simply deploying more GPUs isn't enough. The challenge is making increasingly diverse compute work together.

Gimlet's platform intelligently partitions and routes workloads across heterogeneous hardware, enabling step-function improvements in performance and efficiency. Customers deploy through production-grade APIs without needing to think about hardware selection, placement, or optimization.

We work with foundation labs, hyperscalers, and AI-native companies to power production workloads at massive scale and help define the infrastructure layer for the future of AI.

About the role

We are seeking a Senior Technical Project Manager to lead cross-functional execution, escalation management, and deployment readiness tracking for complex infrastructure programs. This role will coordinate across engineering, supply chain, vendors, deployment teams, operations, and leadership to ensure infrastructure initiatives stay aligned, risks are surfaced early, and blockers are driven to resolution.

The ideal candidate is highly organized, technically fluent, and comfortable operating in fast-moving environments where timelines, vendor dependencies, hardware availability, operational issues, and infrastructure readiness must be tightly managed.

What you will work on

• Build and lead end-to-end project management for AI data center infrastructure deployment programs, from planning through execution and readiness validation.

• Own integrated deployment plans, milestone trackers, risk logs, dependency maps, and executive status reporting.

• Drive readiness tracking across hardware, networking, cabling, site readiness, staffing, logistics, vendor deliverables, and operational dependencies.

• Align engineering, supply chain, procurement, logistics, operations, deployment, finance, external vendors, and customers around execution priorities.

• Manage vendor commitments, delivery timelines, issue follow-up, dependency tracking, and performance visibility.

• Identify timeline risks, supply chain gaps, readiness blockers, and vendor slippage early; coordinate mitigation plans with accountable owners.

• Facilitate cross-functional readiness reviews to unblock issues, confirm decisions, and maintain execution momentum.

• Communicate status, risks, decisions, and escalation needs clearly to technical teams and senior leadership.

• Drive operational issue resolution by clarifying ownership, setting action plans, and following through to closure.

You may be a good fit if

• Experience in technical project management, program management, infrastructure operations, deployment management, or a related role.

• Proven ability to coordinate across hardware vendors, colocation partners, customers, suppliers, logistics, engineering, and deployment operations.

• Working knowledge of power budgeting, rack configuration, GPU cluster networking, and infrastructure deployment dependencies.

• Strong understanding of hardware readiness, supply chain timing, vendor commitments, and operational execution.

• Ability to manage competing priorities, ambiguous blockers, and rapidly changing timelines.

• Excellent written and verbal communication skills, including executive-level status reporting.

• Strong analytical and organizational skills, with experience using project management and reporting tools.

Strong candidates will also have

• Experience with data center deployments, infrastructure builds, hardware rollouts, networking equipment, cabling, GPU clusters, or server environments.

• Familiarity with supply chain constraints, vendor lead times, procurement workflows, and deployment readiness gates.

• PMP, PgMP, Scrum, Agile, or similar project/program management certification.

• Experience supporting global infrastructure programs or multi-site deployments.

What Makes Gimlet Different

Most AI Infrastructure companies are focused on deploying more compute. We are focused on making increasingly diverse compute work together.

We are not building another cloud platform. We are building the orchestration layer for the future of AI infrastructure. We believe the future of AI will require intelligent orchestration across many hardware architectures, datacenters, and execution environments.

The systems we build today will help define how AI workloads are deployed for the next decade