Forward Deployed Engineer

About the Company

We are an early-stage, still-in-stealth team building an AI platform that gives organizations control of their AI through specialized models that are faster, more cost-efficient, and more secure than one-size-fits-all alternatives—and that customers can own and run on their own terms.If you enjoy solving infrastructure challenges, working directly with customers, and bringing AI systems into production, we would love to talk.

Role Overview

As our first Forward Deployed Engineer, you will lead technical deployments and engagements with strategic customers, helping them run our platform reliably within their own infrastructure.Your primary focus will be Kubernetes and infrastructure: configuring deployments, managing upgrades, monitoring system health, and troubleshooting complex issues in customer environments, including closed, on-premises systems. You will investigate challenges across the surrounding infrastructure as well as our platform, working closely with customer technical teams and our engineers to resolve them.This is a highly customer-facing role that combines technical depth with clear communication and sound judgment. As the founding FDE, you will help establish how we deploy, support, and operate our technology with customers, building repeatable processes for future engagements.

Core Responsibilities

• Strategic Customer Engagements: Own the technical relationship throughout deployment and ongoing operations, coordinating with customer stakeholders and internal teams.
• Kubernetes Deployments: Configure, validate, and adapt Kubernetes manifests and deployment settings to each customer’s infrastructure and operational requirements.
• Upgrades and Maintenance: Plan and execute upgrades, manage configuration changes, and verify system health following updates.
• Monitoring and Reliability: Monitor system behavior, resource utilization, and workload patterns; investigate bottlenecks, unusual loads, and reliability issues.
• Infrastructure Troubleshooting: Diagnose and resolve complex problems across Kubernetes clusters, networking, compute, storage, and dependencies within customer environments.
• Deployment Practices: Build runbooks, documentation, and repeatable workflows that improve deployment quality and operational efficiency.
• Automation and Tooling: Write scripts and lightweight tools to simplify configuration, diagnostics, monitoring, and maintenance.

Requirements

• At least 5 years of hands-on software development experience.
• Hands-on experience with Kubernetes in production, including deployment configuration, troubleshooting, and ongoing operations.
• Strong understanding of Linux, containers, networking, and infrastructure fundamentals.
• Ability to investigate complex technical issues across unfamiliar environments and drive them through to resolution.
• Excellent communication and interpersonal skills, with the ability to build trust, explain technical issues clearly, and represent the company professionally.
• Experience collaborating directly with customers or external technical stakeholders.
• Excellent English, including leading technical discussions, presenting solutions, and documenting issues and decisions.
• High ownership, adaptability, and the ability to remain effective when priorities shift or technical challenges arise.
• Ability to write scripts or small tools to automate operational tasks.
• Willingness to travel and work on-site with customers in Israel and abroad, including engagements lasting one week to one month.

Nice to Have

• Experience in forward deployed engineering, solutions engineering, customer-facing infrastructure, DevOps, SRE, or platform engineering.
• Experience operating in enterprise, on-premises, restricted-network, or air-gapped environments.
• Familiarity with GPU infrastructure, AI inference workloads, or workload orchestration platforms such as Run:ai.
• Familiarity with observability tools for metrics, logs, and alerting.
• Software development experience, particularly in Python or Go.
• Understanding of AI models, deployment workflows, or model training.

Prior AI experience is an advantage, but is not required. We value technical resourcefulness, strong customer communication, and the ability to learn quickly.