Resume Score

Check how well your resume matches this job before you apply.

Sign in to check score

About the role

  • Founding Sales Engineer proving Featherless.ai’s open-model inference platform for North American customers. Building demos, benchmarks, POCs, and the company’s sales engineering function.

Responsibilities

  • Partner with the founding Account Executive as the named technical owner on active North American opportunities
  • Run technical discovery covering models, workloads, latency, throughput, spend, and constraints
  • Design and drive proofs of concept and benchmarks against incumbent solutions
  • Build the demo environment and reusable technical collateral
  • Own technical objection handling covering performance, reliability, cost modeling, security, and data handling
  • Lead architecture reviews, live demos, and working-code sessions
  • Build migration paths from closed-model APIs to open weights
  • Run benchmarks and produce throughput, latency, and cost-per-token analyses
  • Scope and execute POCs with clear technical success criteria
  • Write technical sections of proposals, RFP responses, and security questionnaires
  • Support onboarding and first production workloads, then hand off and remain available for expansion
  • Provide structured field feedback to product and engineering
  • Build demo apps, notebooks, reference architectures, integration guides, and internal enablement
  • Represent Featherless at conferences, meetups, and developer events
  • Keep POC and technical-stage details current in HubSpot

Requirements

  • 3–6 years in pre-sales engineering, solutions architecture, or a forward-deployed / customer-facing engineering role
  • Experience at a GPU cloud, inference provider, MLOps platform, AI/developer tooling company, or cloud infrastructure vendor
  • Comfortable writing Python and building demos
  • Working knowledge of modern LLM inference, including vLLM, SGLang, TensorRT-LLM or similar, OpenAI-compatible APIs, quantization, LoRA, fine-tune serving, batching, KV cache behavior, tokens/sec, and cost drivers
  • Practical familiarity with Hugging Face and major open-weight model families
  • Experience evaluating one model against another
  • Comfortable with containers, Kubernetes, cloud networking, and security fundamentals
  • Ability to communicate credibly with ML engineers and CTOs
  • Strong written communication for benchmark writeups and architecture documents
  • Entrepreneurial and self-directed
  • Heavy use of AI tools for research, prototyping, and workflow acceleration
  • Nice to have: experience with AMD GPUs / ROCm
  • Nice to have: exposure to enterprise security and compliance review
  • Nice to have: open-source contributions or public technical writing
  • Nice to have: experience as the first technical hire on a GTM team
  • Must be legally authorized to work in the job's required location without employer visa sponsorship

Benefits

  • Competitive base + variable tied to the team's number
  • Equity
  • Direct work with the CRO and founders
  • Small team, no layers, immediate impact
  • Access to real technical depth: 40,000+ open models and an in-house research team
  • Opportunity to build the sales engineering function
  • Opportunity to represent Featherless at conferences, meetups, and developer events

Job type

Full Time

Experience level

Mid levelSenior

Salary

$150,000 - $190,000 per year

Degree requirement

No Education Requirement

Tech skills

CloudKubernetesPython

Location requirements

RemoteUnited States

Report this job

Found something wrong with the page? Please let us know by submitting a report below.