Sales Engineer – AI Infrastructure

Join a seed‑stage AI infrastructure company building large‑scale training and inference platforms previously accessible only to hyperscalers. The business began with a single managed GPU cluster that reached capacity almost immediately and has since expanded into a global platform spanning infrastructure, networking, and orchestration.

You lead technical discovery, run best‑in‑class demos and proof‑of‑concepts, and partner closely with Sales to drive successful evaluations and long‑term customer expansions.

This is a pre‑sales–forward role for someone who can translate customer needs into clear technical validation, build trust with both executives and engineers, and help create a repeatable technical sales motion across a full‑stack AI platform (hardware + software).

• Partner with Sales to qualify opportunities, lead technical discovery, and define evaluation plans aligned to customer success criteria.
• Design and deliver compelling end‑to‑end demos, tailoring messaging for both technical and executive audiences.
• Own the full technical POC lifecycle: scope definition, success metrics, architecture, timelines, stakeholder alignment, and production handoff.
• Build strong relationships with customer engineering leaders, platform teams, and infrastructure/security owners.
• Translate technical requirements into solution designs tied directly to business outcomes (latency, throughput, cost, reliability, security).
• Create high‑quality enablement assets (demo environments, evaluation playbooks, reference architectures, FAQs) to scale sales effectiveness.
• Provide structured, high‑signal feedback to Product, Engineering, and Research teams based on customer objections, feature gaps, and competitive insights.

• 5+ years in a customer‑facing technical role, including 2+ years in pre‑sales (Sales Engineer, Solutions Architect, or similar).
• Proven experience running complex technical evaluations end‑to‑end and influencing outcomes in enterprise sales cycles.
• Excellent communication skills - able to explain infrastructure and AI concepts to both technical and non‑technical stakeholders.
• Strong knowledge of AI/ML infrastructure and GPU‑based systems, including integration with HPC environments.
• Solid understanding of training, fine‑tuning, and inference workflows for open‑source LLMs.
• Familiarity with Kubernetes, SLURM, Docker/containers, and infrastructure automation or IaC tools (e.g., Ansible).