Sales Engineering Manager leading Zscaler’s cybersecurity and Gen AI portfolio in Canada. Growing the sales engineering team and driving value - based solutions for customers and partners.
About the role
- Founding Sales Engineer proving Featherless’s open-model AI inference platform through demos, benchmarks, and POCs. Partnering with the founding AE across North American customer opportunities.
Responsibilities
- Partner with the founding Account Executive as the named technical owner on 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 for performance, reliability, cost, security, and data handling
- Provide technical input to product and engineering
- 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 defined technical success criteria
- Write technical sections of proposals, RFP responses, and security questionnaires
- Support onboarding and initial production workloads, then hand off for expansion
- Feed structured field input to product and engineering
- Build demo apps, notebooks, reference architectures, integration guides, and internal enablement
- Represent Featherless at conferences, meetups, and developer events
- Maintain POC and technical-stage details 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, and KV cache behavior
- Practical familiarity with the open-model ecosystem, Hugging Face, major open-weight families, and model evaluation
- 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 documentation
- Entrepreneurial and self-directed
- Heavy use of AI tools for research and prototyping
- Nice to have: AMD GPUs/ROCm, enterprise security and compliance review, open-source contributions or public technical writing, or experience as the first technical hire on a GTM team
- Legally authorized to work in the job’s required location without employer visa sponsorship
Benefits
- Competitive base plus variable tied to the team's number
- Equity
- Work directly with the CRO and founders
- Small team with no layers and immediate impact
- Access to real technical depth, including 40,000+ open models and an in-house research team
- Opportunity to build the sales engineering function at a fast-moving AI company
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