Founding Sales Engineer

Featherless AI

Toronto

Remoto

CAD 212.000 - 269.000

Tempo integral

14 dias+

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Resumo da vaga

Featherless.ai is hiring its first Sales Engineer to partner with the founding AE in North America. You’ll be the technical owner for opportunities, mapping workloads, latency, and costs, and driving POCs and benchmarks that show Featherless is faster, cheaper, and more reliable than incumbents.

You’ll build the demo environment, security answers, migration guides, and reusable assets to scale GTM. This role combines deep technical work with customer-facing impact at a fast-growing AI startup.

Qualificações

  • 3–6 years in pre-sales engineering, solutions architecture, or customer-facing engineering roles in AI/ML infra.
  • Hands-on: you write Python and build demos rather than request them.
  • Working knowledge of modern LLM inference stacks and pricing considerations.
  • Familiarity with open-model ecosystems (Hugging Face, open weights).
  • Comfortable with containers, Kubernetes, and cloud networking basics.
  • Credible with both technical and executive audiences.
  • Entrepreneurial and self-directed — you’ll be the first SE and shape the GTM approach.
  • Heavy use of AI tools in your workflow for rapid prototyping.

Responsabilidades

  • Lead the named technical owner role on North American opportunities.
  • Conduct technical discovery: workloads, latency, throughput, spend, and constraints.
  • Design and run POCs and benchmarks to prove Featherless against incumbents.
  • Build the demo environment and reusable technical collateral.
  • Handle technical objections across performance, cost, security, and data handling.
  • Be the field voice into product/engineering and influence roadmap.
  • Write technical sections of proposals and security questionnaires; create a reusable answer library.
  • Support onboarding and first production workloads; ensure smooth handoffs and expansion.
  • Feed product/engineering with field feedback on gaps and needs.
  • Develop scalable technical assets: demos, notebooks, reference architectures, guides.
  • Represent Featherless at conferences and developer events.
  • Keep POC and technical-stage detail current in HubSpot for accurate forecasting.

Conhecimentos

Python
LLM inference
Containers
Kubernetes
Cloud networking
Security basics
Technical writing
AI tooling
Demo development

Ferramentas

Hugging Face
TensorRT-LLM
OpenAI APIs

Descrição da vaga

About Featherless

Featherless.ai is building the world's most reliable open-model inference platform.

About Featherless

Featherless.ai is building the world's most reliable open-model inference platform.

Backed by AMD, Airbus Ventures, 500 Global, Kickstart Ventures, HF0 Residency, Panache Ventures, and Oakseed Ventures, we're a well-funded team of researchers and engineers on a mission to democratize AI through performance and accessibility.

Our cloud provides instant access to 40,000+ open-source AI models and the research innovations powering next-generation efficiency, reliability, and model optimization.

About The Role

We're hiring our first Sales Engineer to pair directly with our founding Account Executive in North America. You are the technical half of a two-person deal team: the AE owns the commercial motion, you own the technical win.

Our buyers are developers, ML engineers, and CTOs, and they don't buy on slides. They buy when someone credible sits with them, looks at their workload, and shows them that open models on Featherless are faster, cheaper, and more reliable than what they're running today. That's your job — hands on keyboard, in the customer's stack, from first technical call through production rollout.

Because you're the first SE here, you'll build the function as you go: the demo environment, the POC playbook, the benchmark harness, the security answers, the migration guides. Every deal you win should make the next one easier to win.

If you like being the person who can actually answer the hard question in the room — and want the technical foundation of a Series A GTM engine to be yours — this is for you.

What You'll Own Immediately
  • Partner with the founding AE as the named technical owner on every active opportunity in North America
  • Run technical discovery: map each prospect's models, workloads, latency and throughput targets, spend, and constraints
  • Design and drive POCs and benchmarks that prove Featherless against the incumbent — closed-model APIs, another inference provider, or self-managed GPUs
  • Build the demo environment and reusable technical collateral that the whole GTM team sells with
  • Own technical objection handling end-to-end: performance, reliability, cost modeling, security, and data handling
  • Be the field's voice into product and engineering — you'll know what we're losing on before anyone else does
Core Responsibilities
  • Lead technical calls tailored to each buyer's stack: architecture reviews, live demos, and working code against their real use case
  • Build migration paths off closed-model APIs and onto open weights — model selection, evaluation, prompt and output parity, cutover plan
  • Run benchmarks and produce the throughput, latency, and cost-per-token analysis that anchors the business case the AE builds
  • Scope and execute POCs with clear technical success criteria, then hold the customer and us to them
  • Write the technical sections of proposals, RFP responses, and security questionnaires; keep a reusable answer library so we never write the same answer twice
  • Support onboarding and first production workloads, then hand off cleanly and stay available for expansion
  • Feed structured field input to product and engineering — feature gaps, model coverage requests, reliability issues, competitive intel
  • Build and maintain the technical assets that scale the team: demo apps, notebooks, reference architectures, integration guides, internal enablement for BDRs and future AEs
  • Represent Featherless technically at conferences, meetups, and developer events
  • Keep POC and technical-stage detail current in HubSpot so forecasting reflects technical reality, not optimism
What You Bring
  • 3–6 years in pre-sales engineering, solutions architecture, or a forward-deployed / customer-facing engineering role — at a GPU cloud, inference provider, MLOps platform, AI/developer tooling company, or cloud infrastructure vendor
  • Genuinely hands-on: you write Python comfortably and build your own demos rather than requesting them
  • Working knowledge of modern LLM inference — serving stacks (vLLM, SGLang, TensorRT-LLM or similar), OpenAI-compatible APIs, quantization, LoRA and fine-tune serving, batching and KV cache behavior, and what actually drives tokens/sec and cost
  • Practical familiarity with the open-model ecosystem: Hugging Face, the major open weight families, and how teams evaluate one model against another
  • Comfortable with containers, Kubernetes, and cloud networking and security fundamentals
  • Credible with both audiences in the same meeting — the ML engineer who wants the numbers and the CTO who wants the risk and cost story
  • Strong written communication: your benchmark writeups and architecture docs should be good enough to forward to a buyer's CEO
  • Entrepreneurial and self-directed — comfortable being the first SE, with no playbook and no one to the escalated the technical answer to
  • Use AI tools heavily in your own workflow to research, prototype, and move faster

Nice to have: experience selling or building on AMD GPUs / ROCm; exposure to enterprise security and compliance review; open-source contributions or public technical writing; experience as the first technical hire on a GTM team.

Why Featherless
  • Build the sales engineering function at a company in one of the fastest-moving spaces in AI
  • Work as a true pair with the founding AE, and directly with the CRO and founders — small team, no layers, immediate impact
  • Real technical depth: 40,000+ open models and an in-house research team shipping inference and optimization work you'll get to sell
  • Be part of a small, high-performing team making open weight AI accessible to everyone
  • Competitive base + variable tied to the team's number, plus equity

Compensation Range: $150K - $190K

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