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 roleYou 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
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.
LLM-serving infra experience (vLLM, TGI, Ray Serve, etc.)
Experience running non-NVIDIA accelerators (TPUs/ASICs) in production.
Skills Required
- Strong systems engineering background with cloud control planes or serving infrastructure at scale
- Comfort working as a high-impact individual contributor rather than a manager
- Track record of building reliability from scratch
- Comfort working with hardware heterogeneity and ambiguity
- Genuine interest in joining an early-stage company of approximately six to seven people
- Experience with LLM-serving infrastructure such as vLLM, TGI, or Ray Serve
- Experience running non-NVIDIA accelerators such as TPUs or ASICs in production
What We Do
General Compute is an AI inference cloud company, positioning itself as the neocloud for alternative chips. The company productionizes purpose-built AI silicon from vendors such as SambaNova, Cerebras, Positron, and d-Matrix by purchasing the racks, securing data center space, and operating the hardware for customers. Its architecture splits prefill on GPUs and decode on specialized accelerators, generating tokens 5-7x faster than GPU-based competitors, serving frontier labs, fast-growing AI application companies, and asset-light clouds.
