Forward Deployed Engineer

Why this role matters

• Own the technical win and the POC timeline, working closely with Sales and Engineering, from call one.
• Design and run reproducible benchmark harnesses (TTFT, ITL, throughput/GPU, p95/p99) and quality-parity evals.
• Run head-to-head bake-offs against leading AI providers — and win them.
• Tune model-to-hardware deployments on B200/B300/GB300 NVL72.
• Build cost-per-token models and write migration plans.
• Handle enterprise security and compliance review, and get deployments to launch readiness.
• Own account health post-signature, driving usage reviews and expansion.
• Turn what you learn into reusable benchmark reports, reference architectures, and AE enablement material.

• Customer-facing engineering with an owned technical outcome at an infrastructure or ML platform company.
• Strong Python skills.
• Dual-audience presence with commercial instinct — credible with a skeptical staff engineer, clear with a CFO, and able to tell a technical objection from a procurement one.

• Hands-on experience with inference internals: vLLM, SGLang, or TRT-LLM, batching, KV cache math, quantization.
• Experience with agentic or coding-assistant workloads at scale.
• Prefix-cache-heavy long context workloads.
• Diffusion image/video, ASR/TTS, or multi-LoRA serving.
• Open-source contributions to vLLM or SGLang.
• Deep NVLink/InfiniBand topology knowledge.