DatologyAI
Forward Deployed AI Engineer (Post-Sales)
$230K–$300K
San Mateo HQ · Hybrid · Full-time · Posted May 27, 2026
- Experience
- 5+ years in technical roles involving solution architecture, customer engineering, consulting, or technical program delivery.
About the job
Guide strategic customers through deploying, operating, and adopting DatologyAI’s data curation platform in on-premises, hybrid, and cloud environments.
What you'll do
- Lead customer onboarding, deployment, production rollout, and long-term adoption as the technical owner for assigned accounts.
- Partner with Sales, Engineering, and Research to translate customer needs into technical plans, support trials, share feedback, and inform roadmap priorities.
- Design and optimize secure, scalable workflows across compute, storage, networking, and distributed systems; report on deployment progress and workload health.
What they ask for
- 5+ years of experience in technical roles involving solution architecture, customer engineering, consulting, or technical program delivery.
- Strong background in distributed systems, data infrastructure, and/or on-prem or hybrid compute environments.
- Experience with ML/AI workflows and systems involving Kubernetes, networking, data pipelines, or large-scale backend infrastructure.
- Deep hands-on experience with multiple cloud platforms (AWS, GCP, Azure), plus expertise in infrastructure-as-code and configuration management for multi-environment deployments.
Pay
$230,000 to $300,000 (base salary)
Tools
AWS, GCP, Azure, Kubernetes, Python, SQL
AI focus
Deploy and support a platform that curates and optimizes training data for AI models; guide customers using it in their ML/AI workflows.
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