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.
About the job
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)
Skills
Python, Kubernetes, Cloud Platforms, Networking, Storage Technologies, Container Orchestration, Infrastructure Deployment, Monitoring, Telemetry, IAM
Similar jobs
Solutions Architecture jobs
Redis
United States
Develop Redis-powered solutions for enterprise customers, lead technical evaluations and pilots, and partner with Sales on account strategy. Requires 3+ years of pre-sales engineering experience, server-side development and Linux expertise, distributed-systems experience, and strong communication skills.
Vitalize
San Francisco, CA
Leads on-site deployments for hospital staffing software, mapping workflows, driving adoption across clinical and ops teams, and building scalable rollout playbooks to activate revenue and ROI.
SnapLogic
United States
Advises enterprise customers on AI adoption by identifying use cases, building prototypes, proving business value, and guiding deployment strategy. Requires hands-on customer advisory experience, strong executive communication, enterprise integration knowledge, and solid AI/LLM expertise.
LangChain
San Francisco, CABuild and deliver production AI agent systems for enterprise customers through architecture advising, co-development, and embedded engineering engagements. Requires 4+ years of software engineering experience, deep Python expertise, and 2+ years shipping production agent systems.
Edia
United States
Build and operate integrations, custom workflows, and full-stack extensions for large school districts, owning deployments from discovery through production stabilization. The role requires 4+ years of software engineering experience, strong debugging and systems skills, and a bachelor’s degree in a rigorous technical field.