AI governance platform for Fortune 500 enterprises, Series A, ~25 people, remote across Europe.
Solutions Engineer
You'll spend your mornings debugging a Python SDK integration with a bank's model pipeline, then hop on calls with their ML engineers to map out how our observability stack catches drift before it hits production. By afternoon you're whiteboarding with a telecom's security team on how to audit LLM prompts across three cloud regions. You're the bridge between raw API capabilities and production-grade AI governance—writing sample code one hour, translating RFP requirements into implementation plans the next. No two days match because no two enterprises deploy AI the same way.
What they're looking for
- 3-8 years in solutions engineering, sales engineering, or forward-deployed engineering for B2B SaaS or data infrastructure
- Fluency in Python and TypeScript; you've shipped production code and can debug a REST integration live on a screen share
- Experience with at least one major cloud provider (AWS, GCP, or Azure) and comfort navigating CI/CD pipelines in enterprise environments
- Track record of owning technical evaluations end-to-end: from first architecture review through security questionnaire to production rollout
- Clear communicator who can earn trust with ML researchers, platform engineers, and procurement teams in the same afternoon