Founding Sales Engineer
Role Overview
This is the company's first Sales Engineer role, paired directly with the founding Account Executive in North America.
The Sales Engineer owns the technical win for buyers including developers, ML engineers, and CTOs.
The role is hands-on in customer environments from the first technical call through production rollout.
The first Sales Engineer will build the demo environment, POC playbook, benchmark harness, security answers, and migration guides.
Key Skills for This Role
Full Job Posting
About Featherless
Featherless.ai builds an open-model inference platform focused on performance, accessibility, reliability, and model optimization.
Its cloud provides access to more than 40,000 open-source AI models and associated research innovations.
About the Role
This is the company's first Sales Engineer role, paired directly with the founding Account Executive in North America.
The Sales Engineer owns the technical win for buyers including developers, ML engineers, and CTOs.
The role is hands-on in customer environments from the first technical call through production rollout.
The first Sales Engineer will build the demo environment, POC playbook, benchmark harness, security answers, and migration guides.
Technical Ownership and Delivery
- Own technical discovery, POCs, benchmarks, demos, migration planning, technical objection handling, and production support.
- Lead technical calls, architecture reviews, live demos, and working-code sessions for customer use cases.
- Create analyses of throughput, latency, and cost per token to support business cases.
- Write technical content for proposals, RFPs, security questionnaires, and reusable answer libraries.
- Maintain demo apps, notebooks, reference architectures, integration guides, and internal technical enablement materials.
- Provide field feedback on product gaps, model coverage, reliability issues, and competitive intelligence.
- Keep technical-stage and POC details current in HubSpot.
- Represent Featherless at technical conferences, meetups, and developer events.
What You Bring
- 3–6 years in pre-sales engineering, solutions architecture, or customer-facing engineering at a relevant infrastructure or AI technology company.
- Hands-on Python development ability and experience building independent demos.
- Working knowledge of modern LLM inference, serving stacks, API compatibility, quantization, LoRA, fine-tune serving, batching, KV cache behavior, throughput, and cost.
- Familiarity with Hugging Face, open-weight model families, and model evaluation.
- Comfort with containers, Kubernetes, cloud networking, and security fundamentals.
- Strong written communication and ability to explain technical performance, risk, and cost to technical and executive stakeholders.
- Entrepreneurial, self-directed approach and heavy use of AI tools for research and prototyping.
Preferred Experience
- Experience selling or building on AMD GPUs or ROCm is preferred.
- Exposure to enterprise security and compliance review is preferred.
- Open-source contributions or public technical writing are preferred.
- Experience as the first technical hire on a GTM team is preferred.
Compensation
- Competitive base pay plus variable compensation tied to the team target and equity.
- The stated compensation range is $150K–$190K, with no pay cadence specified.
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