Founding Sales Engineer

PromptCube; United States; Remoto; USD 150.000 - 190.000; Tempo integral

Benefícios oferecidos por esta vaga

Equity participation

Variable compensation tied to team’s成果

Resumo da vaga

Featherless AI is hiring its first Sales Engineer to pair with the founding AE in North America. You own the technical win from first call through production rollout, building the demo environment, POC playbooks, benchmarks, security answers, and migration guides that scale the GTM team.

As the first SE, you will work directly with developers, ML engineers, and CTOs to prove open-models are faster, cheaper, and more reliable than incumbent solutions. Remote-friendly across US & Canada.

Qualificações

• 3–6 years in pre-sales engineering, solutions architecture or a customer-facing engineering role.
• Hands-on Python with demos rather than requests from others.
• Experience with modern LLM inference stacks and OpenAI-compatible APIs.
• Familiarity with Hugging Face and open-weight families.
• Comfortable with containers, Kubernetes, and cloud networking/security basics.
• Credible communicating to both ML engineers and CTOs.
• Entrepreneurial and self-directed as the first SE on a GTM team.

Responsabilidades

• Lead technical calls tailored to buyer stack: architecture reviews, live demos, and working code against real use cases.
• Build migration paths off closed-model APIs onto open weights; cover model selection, evaluation, prompt/output parity, cutover plan.
• Run benchmarks to analyze throughput, latency, and cost-per-token for business cases.
• Scope and execute POCs with clear technical success criteria; maintain accountability.
• Write technical sections of proposals, RFPs, and security questionnaires; maintain a reusable answer library.

Conhecimentos

Python

Pre-sales engineering

LLM inference knowledge

Containers & Kubernetes

Open-model ecosystem familiarity

Strong written communication

Ferramentas

Hugging Face

TensorRT-LLM

Descrição da vaga

Role overview

Featherless AI's founding Sales Engineer role is remote-eligible for North America-based candidates with valid work authorization, serving as the technical half of the deal team to demonstrate open-model inference value to developers, ML engineers, and CTOs through hands-on technical discovery, POCs, and benchmarks.

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 Featherless AI to them
• Write the technical sections of proposals, RFP responses, and security questionnaires; maintain a reusable answer library so answers are never duplicated

Qualifications

• 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: 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
• Practical familiarity with the open-model ecosystem: Hugging Face, 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: 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 escalate the technical answer to

Application conditions

• Applicants must verify residency and work authorization eligibility for listed North America locations or meet remote time zone and travel requirements specified in the original posting
• Position is listed for specific locations across US and Canada including Atlanta, Tampa, Miami, Orlando, Ottawa, NYC, Salt Lake City, Nashville, Ashburn, Austin, Montreal, Toronto, Halifax, Charlotte, Seattle, DFW, Fairfax, Boston, Raleigh, Washington, Chicago, Phoenix, Scottsdale, Denver, Vancouver; remote does not imply worldwide eligibility
• Check original listing for specific residency, work authorization, time zone, language and travel requirements before applying
• Employment type is full-time per the original listing

Preferred qualifications

• 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

Compensation and benefits

• $150K - $190K USD per year
• Equity participation
• Variable compensation tied to the team's number

What this role focuses on

• As the first Sales Engineer, you will own the technical win from first customer call through production rollout, building the demo environment, POC playbook, benchmark harness, security answers, and migration guides that scale the GTM team

Application preparation (editorial suggestions)

• Confirm your residency and work authorization status covers one of the listed North America locations or meets remote eligibility criteria before applying
• Prepare concrete examples of benchmarking open-model performance against closed-model APIs or self-managed GPUs using Python and LLM inference stacks

Employer-published remote role. Listed location(s): Remote (US & Canada); Atlanta; Tampa; Miami; Orlando; Ottawa; New York City; Salt Lake City; Nashville; Ashburn; Austin; Montreal; Toronto; Halifax; Charlotte; Seattle; Dallas-Fort Worth; Fairfax; Boston; Raleigh; Washington; Chicago; Phoenix; Scottsdale; Denver; Vancouver. Remote does not imply worldwide eligibility. Check the original listing for residency, work authorization, time zone, language and travel requirements.

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 escalate 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