Moving from first silicon to factory ramp, and from the ODM to a live fleet, dictates an unforgiving timeline. Server-Craft provides the execution engine to bridge these critical handoffs. Through rigorous rack bring-up, NPI execution, customer-site turn-up, and continuous reliability engineering, complex hardware is seamlessly transformed into deployable, resilient infrastructure.
Real results from custom accelerator deployments — rack bring-up, factory ramp, field deployment, and fleet reliability. Team backgrounds include NVIDIA, Oracle, Supermicro, and leading AI hardware startups — bringing the execution standards of large-scale fleet programs to early-stage deployments.
Established critical material controls and designed multiple high-capacity production lines. Accelerated physical provisioning and infrastructure readiness for software engineering deployments within heavily compressed timelines.
Directed the end-to-end NPI process for next-generation AI systems, transitioning from prototype to full rack-scale deployment. Ramped cross-functional teams to ensure seamless factory execution on aggressive schedules.
Led the technical strategy for factory yield improvement during flagship NPI ramps. Engineered triage methodologies for complex failures and scaled systemic rework processes, recovering millions in inventory value and accelerating delivery.
Validated high-speed fabric performance (BER, FEC) for dense AI racks, enabling stable scale-out bring-up and memory sharing across next-generation compute nodes.
Created rapid production capacity by scaling deployment throughput to deliver critical fleet infrastructure in under a week, keeping strict engineering and validation milestones on track.
Restored benchmark cluster functionality by isolating and resolving issues across critical AI infrastructure—including advanced liquid cooling and power delivery systems—preventing validation downtime.
Directed end-to-end system validation for high-density compute platforms. Isolated and resolved complex hardware-firmware interactions, signal integrity bottlenecks, and thermal limits during early bring-up, ensuring platform stability and performance before volume production.
Managed technical alignment between internal engineering and external contract manufacturers (CMs), driving continuous process improvements and ensuring strict quality control during early-stage production.
Standardized manufacturing processes for contract manufacturers by developing a full library of assembly/disassembly SOPs and rework instructions, ensuring consistent quality for high-volume builds.
Transforming first-silicon prototypes into deployable, repeatable infrastructure—and sustaining fleet reliability in the field.
Designing and standing up dedicated triage teams to coordinate debug across validation, factory, and field environments. Structuring the escalation path and assigning targeted engineering resources to drastically reduce turnaround time on system failures.
Power sequencing, board-level diagnostics, link training, and acceptance testing. Transforming early-stage heroics into signed-off, repeatable procedures for technicians.
Test coverage and yield feedback loops with ODMs and CMs. First-article inspection, line qualification, and a clean escalation path from the factory floor back to core design and validation teams.
On-site integration at customer and colo facilities: power, cooling, cabling, network handoff, and acceptance criteria the customer signs.
Analyzing scale-out topologies, switch tiers, and optical interconnects to diagnose performance bottlenecks and isolate fabric faults across the cluster.
Verification that electronics and interfaces meet design specifications, while testing underlying code and logic operate as intended.
Proprietary bring-up automation, monitoring integration, and internal tooling designed to execute deployments with speed and absolute consistency.
Long-term support for mature platforms after core engineering teams transition to future products. Taking ownership of EOL component management, lingering firmware resolution, and fleet stability to keep current generations running at scale.
Executing rapid triage and scalable rework strategies to recover stalled inventory, unblock factory throughput, and restore critical capital value.
We partner with teams shipping novel accelerator hardware from first silicon — and the operators, manufacturers, and facilities running the first fleets.
From first silicon to first rack: bring-up, validation, and ramp support.
Yield recovery, line qualification, and test coverage feedback during high-volume ramps.
On-site power, cooling, cabling, and network handoff with signed acceptance.
Fleet reliability, failure analysis, and runbooks that keep deployed infrastructure running.
Deploying and sustaining specialized compute fleets at customer and colo sites.
Co-Founder · Design · Bring-up, validation, debug, and sustaining
Previously led triage team for NVIDIA's flagship HGX and DGX programs, taking hundreds of high-density AI systems from first-article module and tray validation up to full L11 rack deployment. Operationalized makeshift lab production lines that consistently outpaced factory timelines, including the rapid triage, rework, and redeployment of 500+ next-generation compute nodes in under seven days.
Co-Founder · Bring-up, validation, debug, and sustaining
14 years in NPI and systems validation at NVIDIA and Supermicro, including the flagship DGX and HGX AI platform ramps. Built the automated reliability testing and failure-analysis loops that drove critical hardware and firmware solutions directly back to R&D.
Co-Founder · AI Infrastructure Bringup and Validation
6+ years in AI infrastructure and datacenter systems engineering across cloud, semiconductor, and AI hardware environments. Improves the reliability, scalability, and accessibility of advanced compute systems through deep system triage and cross-layer debugging — spanning hardware, firmware, high-speed interconnects, platform software, and rack-scale infrastructure. Takes complex accelerator platforms from early bring-up and failure isolation to repeatable, production-ready deployment.
The decision to externalize execution is driven by scale and engineering bandwidth. Every hour a design or validation engineer spends debugging is an hour lost on the next architecture. Furthermore, fleet deployment capacity must fundamentally scale faster than internal headcount can be hired and trained.
Silicon and systems engineers stay on the roadmap instead of absorbing field escalations.
Scale the team to the shipment schedule without carrying headcount between ramps.
Resolving complex dependencies through a single, cross-discipline triage operation rather than fragmented engineering silos.
Direct integration into existing VPNs and toolchains, eliminating parallel infrastructure and onboarding delays to deliver utility from day one.
Rapid anomaly triage against fixed GTM and customer acceptance deadlines.
Internal runbooks and automated test coverage are engineered to accelerate execution. This rigorous internal standardization guarantees rapid, zero-variance deployment of the final system.
Operational constraints vary from early-stage factory NPI to late-stage fleet deployment. Initiate a technical discovery consultation to evaluate current infrastructure pain points. A brief engineering review ensures the precise alignment of targeted services to unblock bandwidth and accelerate timelines.
contact@server-craft.comSan Jose, California · Response within one business day