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General Compute

engineering opportunity

Founding Platform Engineer

You will build and own the inference cloud control plane, API, and serving layer to manage a heterogeneous fleet of GPUs and ASICs. You will also be responsible for scaling the platform, ensuring reliability, and partnering with deployment teams.

San Francisco, California, United StatesremoteFULL_TIME

Posted

About the role

What will you do at General Compute?

About us

General Compute is the neocloud for alternative chips.

Inference is fragmenting: purpose-built silicon from SambaNova, Cerebras, Positron, d-Matrix, and others already beats GPUs on decode, and we productionize that hardware — we buy the racks, find the data center space, and run it for our customers. Each piece of hardware runs the workload it's actually built for: prefill stays on GPUs, decode moves to the chip built for it, and today that means generating tokens 5–7× faster than existing GPU-based competitors.

Our customers are frontier labs, fast-growing AI application companies, and asset-light clouds.

We closed a $15M seed round in May 2026, and have since closed a $400M debt facility — $100M funded upfront by Upper90, with the balance available for drawdown — collateralized by our inference chips.

About the role

You will build the inference cloud itself — the control plane, API, and serving layer that turn racks into a sellable product. There's no existing platform team to inherit or manage, no legacy system to work around, and no established playbook to follow — just the platform itself to build, with reliability treated as core infrastructure from day one rather than something bolted on after the first outage.The technical problem is also genuinely unsolved elsewhere.

The fleet is heterogeneous by design — GPUs for prefill, multiple ASIC vendors for decode — so there's no single-vendor playbook to lean on; you'll be defining how a mixed-hardware inference cloud gets scheduled, routed, and served reliably, in close partnership with the teams standing up the physical fleet.

What you'll do:

Build/own the control plane — routing, model placement, scheduling across a mixed ASIC/GPU pool

Build the API and serving layer exposing rack capacity as a sellable product

Build in reliability and observability from day one

Scale the platform ahead of the demand curve

Partner closely with data center deployment and model bring-up teams

Be a founding technical voice on platform architecture

What we need from you:

Strong systems engineering background on cloud control planes/serving infra at scale

Comfort being a high-impact IC rather than a manager

Track record building reliability from scratch

Comfort with hardware heterogeneity/ambiguity

Genuine interest in being an early hire at a ~6–7 person company.

Nice-to-haves:

LLM-serving infra experience (vLLM, TGI, Ray Serve, etc.)

Experience running non-NVIDIA accelerators (TPUs/ASICs) in production.

Which skills does this role require?

Platform EngineeringCloud Control PlanesServing InfrastructureSystems EngineeringReliability EngineeringObservabilityHardware HeterogeneityAPI DevelopmentModel PlacementSchedulingASICGPULLM ServingvLLMTGIRay ServePlatform EngineerInference CloudControl PlaneAPIServing LayerReliabilityHeterogeneous FleetSambaNovaCerebrasPositrond-MatrixLLMInfrastructureCloud ComputingData CenterModel Bring-upArchitectureStartupLLMs

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Identify the requirements you can demonstrate, then choose examples from your work to discuss with the hiring team.

Review the responsibilities and requirements before adding an opening to your shortlist.

Role information can change. Confirm current details on the original application page.

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