Forward Deployed Engineer – Infrastructure and Deployment

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Preql AI

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2022

🤖 Artificial Intelligence

☁️ SaaS

🏢 Enterprise

Artificial Intelligence • SaaS • Enterprise

Preql AI is an enterprise-focused AI data platform that automates the hardest parts of AI adoption by cleaning, reconciling, and contextualizing messy data across ERP, CRM, HR, and expense systems. Using agentic semantic modeling and continuous data-cleaning agents, it creates auditable, AI-ready pipelines and structured outputs for copilots, dashboards, and decision workflows, with enterprise-grade security, governance, and quick integrations for finance, operations, and technology teams.

📋 Description

• Own installation and configuration of Preql in customer environments, including Docker images, Helm charts, and deployment into customer-managed Kubernetes across AWS, Azure, GCP, and on-premise • Set up networking, identity, and access, including private connectivity, SSO and SAML, IAM and role design, warehouse permissions, and secrets management • Own deployment architecture for each account and ensure the delivered build matches the SOW scope • Navigate customer IT environments to proactively uncover and resolve potential blockers • Lead enterprise security and compliance reviews, including questionnaires, data handling and residency requirements, architecture walkthroughs, and escalations • Maintain production health in customer environments through monitoring, upgrades, and first response to incidents • Enforce release and versioning discipline so customers remain on known, supportable configurations • Create runbooks, installation automation, and reference architecture documentation • Independently run customer installations and explain Preql’s architecture to customer security teams • Reduce installation time, maintain known versions, and make deployment a repeatable process

🎯 Requirements

• 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 experience, including VPCs, private connectivity, SSO, SAML, IAM, role design, and secrets management • Experience with CI/CD, observability, and incident response • High SQL and data infrastructure literacy • Comfort working directly with customers, including scoping, pushing back, and delivering bad news early • High tolerance for ambiguity and ability to create runbooks where none exist • Strong signal: experience packaging and shipping self-hosted or customer-managed software • Strong signal: experience carrying deployments through regulated buyers’ security reviews • Strong signal: familiarity with enterprise data infrastructure and finance systems