Founding AI Sales Engineer — Build the Technical GTM Engine

Featherless AI; Denver (CO); On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Competitive base + equity

Small team, immediate impact

Job summary

Featherless AI is hiring its first Sales Engineer to partner with the founding Account Executive in North America. You will be the technical owner on opportunities, conducting discovery, designing POCs, and delivering benchmarks that prove Featherless faster, cheaper, and more reliable than incumbents.

You’ll build the demo environment and collateral while addressing security, cost, and performance questions.

Qualifications

• 3–6 years in pre-sales engineering or related customer-facing roles.
• Hands-on Python and demo-building ability.
• Experience with modern LLM inference stacks and OpenAI-compatible APIs.
• Familiarity with Hugging Face open weights and evaluation.
• Comfortable with containers, Kubernetes, and cloud networking basics.

Responsibilities

• Lead technical calls tailored to buyer's stack with architecture reviews and live demos.
• Build migration paths off closed-model APIs to open weights and evaluate models.
• Run benchmarks for throughput, latency, and cost-per-token analysis.
• Scope and execute POCs with clear success criteria and reusable technical collateral.
• Write technical sections of proposals and security questionnaires; maintain a reusable knowledge base.
• Support onboarding and first production workloads and hand off cleanly for expansion.

Skills

Python

LLM inference

Demos

Benchmarks

Kubernetes

Tools

Open-model platforms

Hugging Face

OpenAI-compatible APIs

Job description

Featherless AI is hiring its first Sales Engineer to partner with the founding Account Executive in North America. You will be the technical owner on opportunities, conducting discovery, designing POCs, and delivering benchmarks that prove Featherless faster, cheaper, and more reliable than incumbents.

You’ll build the demo environment and collateral while addressing security, cost, and performance questions.