Solutions Engineer

Role overview Help customers evaluate and adopt a technical product for understanding and reducing waste in GPU workloads. You’ll guide deployments from initial infrastructure access to useful findings, while connecting customer needs with product and engineering teams.

Responsibilities - Lead customer onboarding, including environment access, deployment, and surfacing initial recommendations. - Investigate GPU usage and waste in customer environments, then explain practical opportunities to improve utilization. - Work with engineering to address product gaps uncovered during deployments. - Create repeatable onboarding guides, playbooks, and technical documentation. - Lead discovery conversations and technical demonstrations for prospective cloud providers and enterprise AI teams.

Requirements - At least three years in solutions engineering, customer engineering, or technical account management. - Practical experience with Kubernetes and a major cloud platform such as AWS, GCP, or Azure. - Familiarity with AI/ML infrastructure, including model serving, GPU utilization, or inference optimization. - Ability to read Python and YAML and write light scripts for customer environments. - Strong communication skills across technical discussions and executive demonstrations. - Experience working with early-stage products and building processes where established playbooks are not yet available.

Benefits and work setup - Full-time, remote role based in the US.