Senior Hardware Systems Engineer — AI Infrastructure

Build the operating system for autonomous AI infrastructure.

Datafabrix sits at the intersection of high-speed hardware, embedded telemetry, AI analytics, and cloud orchestration. We are building a team that wants difficult systems problems, direct customer impact, and a high bar for engineering clarity.

San Jose, California | On‑site or hybrid depending on role | Hardware + software + AI infrastructure

The product is not a thin SaaS layer. It is a coordinated stack: smart hardware, embedded telemetry, AI infrastructure intelligence, and a cloud control plane. We are looking for people who want direct ownership and real systems work.

• High‑consequence systems work. Thermal, hardware, telemetry, and software decisions all connect to customer outcomes.
• Clear ownership. We prefer people who can define the next step and move a problem to closure.
• Technical honesty. We value direct reasoning, defensible decisions, and a willingness to challenge weak assumptions.
• Meaningful upside. Compensation is designed to be competitive for the stage, with meaningful equity for builders.

The profiles we tend to respond to fastest include Board Design, Signal Integrity, Embedded Telemetry, Firmware, Platform Engineering, Data Pipelines, AI Infrastructure Analytics, and Customer Engineering. If your background does not map exactly to one title but clearly aligns with these areas, still reach out. Strong systems builders rarely fit into a narrow keyword box.

Representative roles we are prioritizing. These are the kinds of profiles we are most likely to engage quickly. If your experience overlaps substantially, reach out directly even if your exact title differs.

Own critical portions of the high‑speed hardware foundation, from design tradeoffs through validation thinking and deployment readiness.

San Jose / Hybrid, Full‑time (PCIe / Board Design)

• Translate product requirements into board‑level architecture and validation priorities.
• Work across signal integrity, thermals, mechanical constraints, and production‑readiness decisions.
• Collaborate tightly with firmware and platform teams so telemetry and hardware behaviors remain aligned.

Build the low‑level software layer that turns deployed hardware into usable telemetry, diagnostics, and control signals for the platform.

San Jose / On‑site preferred, Full‑time (Firmware / Telemetry)

• Develop instrumentation, device interfaces, and observability hooks close to the hardware.
• Improve reliability, diagnostics, and recoverability under real operating conditions.
• Partner with analytics and cloud teams to keep data pipelines trustworthy from source to dashboard.

Design backend and control‑plane systems that convert infrastructure telemetry into actionable fleet management, policy, and workflow software.

Hybrid by role, Full‑time (Backend / Cloud)

• Build APIs, services, and operator‑facing workflows around infrastructure health and automation.
• Work on architectures that remain understandable under enterprise‑scale operational complexity.
• Balance delivery speed with reliability, observability, and long‑term maintainability.

Build the data layer that connects telemetry streams, model inputs, and operator workflows across the Datafabrix platform.

Hybrid by role, Full‑time (Data / AI Infrastructure)

• Design ingestion and transformation pipelines for infrastructure telemetry at production quality.
• Partner with product and engineering to surface the signals that actually matter to operators.
• Help create the data foundation for predictive and autonomous infrastructure intelligence.

• Initial conversation. We discuss your background, the role fit, and the systems problems you have actually solved.
• Final alignment. We close on expectations, scope, work model, and why the role matters at this stage.

Send a short introduction, résumé or Linked In profile, and any work samples that help us understand your depth.

Not always. We care most about deep systems ability, strong engineering judgment, and evidence that you can work effectively at the boundary between technical layers.

It depends on the role. Hardware‑heavy positions typically benefit from more on‑site time, while some software and data roles can support more hybrid flexibility.

Yes. If your profile is directionally strong and your work maps clearly to the problems we are solving, send an application anyway.

If you want to work on the infrastructure layer of AI with a team that values technical depth, ownership, and execution, send a note. We read every serious application.