Forward Deployed Engineer, Infrastructure and Deployment
AI summary of the role
Forward Deployed Engineer owning installation, security, upgrades, and health of Preql's self-hosted software in regulated enterprise customer environments.
What you’ll do
- Install and configure Preql in customer environments using Docker images, Helm charts, and customer-managed Kubernetes across AWS, Azure, GCP, and on-premise.
- Set up networking, identity, and access: private connectivity, SSO/SAML, IAM, warehouse permissions, secrets management.
- Own deployment architecture per account, ensuring SOW scope matches what is built.
- Navigate customer IT environments to proactively uncover and resolve blockers.
What you’ll bring
- 5+ years in infrastructure, platform, or DevOps engineering shipping into production environments you did not control.
- Production experience with Docker and Kubernetes.
- Depth in at least one of AWS, Azure, or GCP, with working understanding of the others.
- Enterprise networking and identity: VPCs, private connectivity, SSO/SAML, IAM, secrets management.
Technologies
Docker · Kubernetes · Helm · AWS · Azure · GCP · SSO · SAML · IAM · VPC · CI/CD · observability
Source and classification
Implementation & delivery · Evidence for this classification:
About Preql Preql helps enterprises clean, unify, and govern messy internal data so it actually works for AI, analytics, and reporting. We work with large organizations navigating complex data environments and high-stakes operational workflows. Based in New York, our team comes from data infrastructure, AI, and enterprise software. How we work We’re a small team with little bureaucracy. Leadership expects individuals to take ownership, move quickly, and make good decisions for the company with support from their teammates. The curious do well here, are comfortable operating in ambiguity, and are willing to form opinions and act on their convictions instead of waiting for instructions. The role We ship self-hosted software into regulated enterprises. That means every deployment involves someone else's Kubernetes cluster, someone else's identity provider, someone else's network
More from the job description
About Preql Preql helps enterprises clean, unify, and govern messy internal data so it actually works for AI, analytics, and reporting. We work with large organizations navigating complex data environments and high-stakes operational workflows. Based in New York, our team comes from data infrastructure, AI, and enterprise software. How we work We’re a small team with little bureaucracy. Leadership expects individuals to take ownership, move quickly, and make good decisions for the company with support from their teammates. The curious do well here, are comfortable operating in ambiguity, and are willing to form opinions and act on their convictions instead of waiting for instructions. The role We ship self-hosted software into regulated enterprises. That means every deployment involves someone else's Kubernetes cluster, someone else's identity provider, someone else's network policy, and a security team that has to sign off before any of it runs. You will own how Preql gets installed, secured, upgraded, and kept healthy in customer environments. What you will own Installation and configuration of Preql in customer environments: our Docker images and Helm charts, deployment into customer managed Kubernetes across AWS, Azure, GCP, and on-premise Networking, identity, and access setup: private connectivity, SSO and SAML, IAM and role design, warehouse permissions, secrets [... source excerpt omitted ...] agement The deployment architecture for each account, including choosing the right configuration and making sure what is scoped in the SOW is what actually gets built Navigating customer IT environments to proactively uncover and resolve potential blockers Enterprise security and compliance review: questionnaires, data handling and residency requirements, architecture walkthroughs with customer security teams, and the escalations that come with regulated buyers Production health in customer environments: monitoring, upgrades, and first response when something breaks, rather than escalating straight to product engineering Release and versioning discipline that keeps every cus [... source excerpt omitted ...] on that make each deployment faster than the last What success looks like 90 days: you have run an install end to end without product engineering in the room, and you can walk a customer's security team through our architecture yourself 6 months: install time for a comparable customer has dropped measurably, every account is on a known version, and there is a runbook that did not exist before 12 months: deployment is a repeatable process rather than a project, and product engineers are not being pulled into customer environments What we are looking for 5+ years in infrastructure, platform, or DevOps engineering, shipping into production environments you did not control Doc
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