Sales Engineer (AI/ML Inference) at Featherless.ai

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, they are a well-funded team of researchers and engineers on a mission to democratize AI through performance and accessibility. Their cloud provides instant access to 40,000+ open-source AI models and cutting-edge research innovations for next-generation efficiency, reliability, and model optimization.

About the Role

Featherless is hiring their first Sales Engineer to partner directly with the founding Account Executive in North America. This role is the technical half of a two-person deal team, where you will own the technical win while the AE handles the commercial motion.

Buyers are developers, ML engineers, and CTOs, who don’t buy based on slides alone. Instead, they buy when someone credible engages directly with their workload and demonstrates that open models on Featherless are faster, cheaper, and more reliable than their current solutions. Your job is hands-on: from the first technical call through production rollout.

As the first Sales Engineer, you’ll build the function from the ground up, creating the demo environment, POC playbook, benchmark harness, security answers, and migration guides. Each deal you win should streamline the process for future wins.

What You'll Own Immediately

• Partner with the founding AE as the named technical owner on every active opportunity in North America
• Conduct technical discovery to map each prospect's models, workloads, latency and throughput targets, spend, and constraints
• Design and execute POCs and benchmarks to prove Featherless against incumbents, including closed-model APIs, other inference providers, or self-managed GPUs
• Build the demo environment and reusable technical collateral for the entire GTM team
• Handle technical objections end-to-end, covering performance, reliability, cost modeling, security, and data handling
• Serve as the field's voice into product and engineering, identifying gaps and competitive intel before others

Core Responsibilities

• Lead technical calls tailored to each buyer's stack, including architecture reviews, live demos, and working code against their real use case
• Build migration paths off closed-model APIs and onto open weights, including model selection, evaluation, prompt and output parity, and cutover plans
• Run benchmarks and produce throughput, latency, and cost-per-token analysis to anchor the business case
• Scope and execute POCs with clear technical success criteria, ensuring accountability for both the customer and Featherless
• Write technical sections of proposals, RFP responses, and security questionnaires, maintaining a reusable answer library
• Support onboarding and first production workloads, then hand off cleanly while staying available for expansion
• Provide structured field input to product and engineering, including feature gaps, model coverage requests, reliability issues, and competitive intel
• Build and maintain technical assets like demo apps, notebooks, reference architectures, integration guides, and internal enablement for BDRs and future AEs
• Represent Featherless technically at conferences, meetups, and developer events
• Keep technical details current in HubSpot to ensure forecasting reflects reality

What You Bring

• 3–6 years in pre-sales engineering, solutions architecture, or a forward-deployed/customer-facing engineering role, preferably in GPU cloud, inference provider, MLOps platform, AI/developer tooling, or cloud infrastructure
• Genuinely hands-on with Python and comfortable building your own demos rather than requesting them
• Working knowledge of modern LLM inference, including serving stacks (vLLM, SGLang, TensorRT-LLM), OpenAI-compatible APIs, quantization, LoRA and fine-tune serving, batching, KV cache behavior, and factors driving tokens/sec and cost
• Practical familiarity with the open-model ecosystem, including Hugging Face and major open weight families, and how teams evaluate models
• Comfortable with containers, Kubernetes, and cloud networking and security fundamentals
• Credible with both technical and executive audiences, addressing the ML engineer's needs for numbers and the CTO's concerns about risk and cost
• Strong written communication skills, with benchmark writeups and architecture docs suitable for forwarding to a buyer's CEO
• Entrepreneurial and self-directed, comfortable being the first Sales Engineer with no playbook or escalation path
• Heavy use of AI tools in your workflow for research, prototyping, and faster execution

Nice to have: experience selling or building on AMD GPUs/ROCm, exposure to enterprise security and compliance review, open-source contributions, public technical writing, or 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, in a small team with immediate impact
• Engage with real technical depth, including access to 40,000+ open models and in-house research innovations
• Be part of a small, high-performing team making open-weight AI accessible to everyone
• Competitive base salary + variable tied to team performance, plus equity