Solutions Architect, AI Infrastructure

Touchdown Labs, Inc.; Santa Clara (CA); On-site; USD 150,000 - 195,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

Touchdown Labs is seeking a Solutions Architect for AI Infrastructure in Santa Clara, CA. You will design the right AI infrastructure for each customer before engagement, combining cloud, on-premise, and hybrid architectures to meet cost and latency targets.

You bring 5+ years in solutions architecture, infrastructure, or ML systems, with a strong grasp of cloud platforms, Kubernetes, and GPU serving. Inference serving frameworks experience is a plus, and you’ll work with partners and vendors

Qualifications

• 5+ years in solutions architecture, infrastructure, or ML systems.
• Strong grasp of cloud, Kubernetes and GPU serving fundamentals.
• Experience with inference serving frameworks.

Responsibilities

• Discovery and architecture design.
• Capacity, cost, and latency estimates.
• Technical support for sales.
• Hand scoped work to forward deployed engineers.

Skills

Solutions architecture

Infrastructure

ML systems

Cloud platforms

Kubernetes

GPU serving

Inference serving frameworks

Job description

# Solutions Architect, AI InfrastructureDesign the right AI infrastructure for each customer before work starts.**Location:** Santa Clara, CAAll roles →Apply for this role →---SeniorSanta ClaraOpenings: MultipleOpen role## Solutions Architect, AI Infrastructure### Our missionAI is becoming fundamental to how the world works. When it is, the ability to compute, and to manufacture the hardware that computes, should not be concentrated in a few places. Touchdown's mission is to make compute accessible to the whole world and to reindustrialize advanced semiconductor manufacturing in the United States. We co-design everything for next-generation compute: the AI systems people use, the software that serves them, the architectures and chips underneath, and the packaging, test, and manufacturing that make them real. Co-design brings down the complexity and cost of building compute. That is what makes manufacturing in America competitive again, and what puts compute within reach of people and companies everywhere. We build alongside the world's best manufacturing ecosystems, including Taiwan's, and every role here makes one layer better and carries what it learns to the rest.### Why this role mattersThe right system design for a customer depends on models, software, and hardware together. Solutions architects make that whole-stack decision before work starts.### Technical scopeTechnical discovery; architecture across cloud, on-premises, and hybrid; model and serving choices; capacity, cost, and latency estimation; reference architectures; technical support for sales and handoff to delivery.### First 90 days* Run technical discovery and write architecture recommendations.* Build reference architectures with measured cost and latency.* Hand scoped work to forward deployed engineers.### What you will own* Discovery and architecture design.* Capacity, cost, and latency estimates.* Technical support for sales.### What you bring* 5+ years in solutions architecture, infrastructure, or ML systems.* Cloud, Kubernetes, and GPU serving fundamentals.### Helpful experience* Inference serving frameworks### How we work* AI-native by default. You use coding agents, AI-assisted analysis, and automation every day, and you check their output against measurements before anyone relies on it.* We work alongside foundries, test houses, OSATs, and research labs, and we build with partners rather than against them.### How the role works* Full-time.* Location: Santa Clara, CA.* Openings: Multiple.* Pay: $150,000–$195,000 base (Santa Clara, CA), plus variable compensation.* Ranges are base pay for U.S. roles and depend on location, experience, and level. Full-time roles also include equity and benefits. Taiwan pay is set to the local market and discussed in the first call.* Start date and employment details are discussed during the process.Apply for this role →Applications are reviewed against the work described here. We do not use a degree, title, or keyword list as a substitute for evidence.