Forward Deployed Engineer, Infrastructure Specialist
Lead end-to-end deployments of Reducto's AI document platform into customer VPCs and on-prem environments. Hands-on infrastructure work bridging enterprise IT, security, and platform teams with 5+ years production ops experience.
Responsibilities
- Lead end-to-end deployment of Reducto into customer environments (VPC to bare metal on-prem), including planning, configuration, testing, and rollout
- Partner with enterprise IT, security, and platform teams to assess infrastructure, security posture, and data management practices; design tailored deployment strategies
- Understand hardware powering in-house ML models to successfully deploy them onto customer infrastructure
- Build monitoring, telemetry, and phone-home patterns that provide visibility into customer-controlled environments without compromising security posture
- Debug and resolve customer-specific infrastructure issues end-to-end (K8s misconfigurations, cloud IAM edge cases), minimizing customer downtime
- Own incident response for customer deployments with world-class operational excellence
- Codify repeatable deployment patterns, runbooks, and automation to scale across future deployments
Requirements
- 5+ years of hands-on experience operating production infrastructure, including deploying software into environments you don't fully control
- Comfortable with Python or similar languages
- Exceptional at working across cloud platforms, container orchestration (Kubernetes), networking, and storage technologies
- Clear communication with external engineers; able to diagnose problems live with customer platform teams
- Energized by owning customer problems end-to-end
- Build your own tools on the fly to diagnose, experiment, and address reliability problems (dashboards, automated remediation workflows)
- Quantitative, hands-on approach to system operations, automation, and continuous improvement
Nice-to-Haves
- Deployed software into regulated environments (financial services, healthcare, legal, insurance) with complex infrastructure
- Experience with Replicated/KOTS, Helm, or similar enterprise distribution tooling
- Experience with GPU infrastructure, model serving, or AI/ML workload deployment patterns on customer-controlled hardware
- Prior experience at an early-stage, high-growth company (founder, founding engineer, or early deployment hire)
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