Forward Deployed Engineer - Physical AI Cloud Platform

Role description

Role Overview

The Forward Deployed Engineer, Cloud Platform is a senior, high-autonomy individual contributor role that owns the infrastructure foundation making the physical AI platform fast, reliable, scalable, secure, and cost-effective. This role sits with strategic customers and ISV partners, embedded directly inside their engineering teams, and ships production infrastructure that lets customers run real physical AI workloads, not just demos.

What You Will Do

End-to-End Ownership Inside Strategic Accounts: Own discovery, technical scoping, infrastructure design, build, and production rollout for each design partner and ISV engagement, translating ambiguous infrastructure problems into deployable production systems. Build and operate the cloud infrastructure that powers customer physical AI workflows. Own compute orchestration for simulation, training, evaluation, inference, and batch workloads, not just what runs, but how it runs at scale.

Why It Might Be a Fit

We expect you to have 6+ Years of Hands-On Engineering: Strong backend, cloud infrastructure, platform engineering, or SRE experience, with at least two years in a customer-facing or deployment-oriented technical role. Strong Systems Programming: Strong Python, Go, or similar systems and backend programming skills. AI-Native Development Workflow: Fluency in modern AI coding tools (Claude Code, Codex, Cursor) as primary leverage to rapidly design, implement, test, debug, and refactor production-quality software.

Requirements

• 6+ Years of Hands-On Engineering: Strong backend, cloud infrastructure, platform engineering, or SRE experience
• Distributed Systems & Compute Platforms: Experience building distributed systems, job orchestration, compute platforms, internal developer platforms, or ML infrastructure
• Strong Systems Programming: Strong Python, Go, or similar systems and backend programming skills
• AI-Native Development Workflow: Fluency in modern AI coding tools (Claude Code, Codex, Cursor) as primary leverage to rapidly design, implement, test, debug, and refactor production-quality software
• Cloud-Native Toolchain: Experience with Kubernetes, containers, CI/CD, observability, cloud networking, storage, IAM/RBAC, and infrastructure as code
• GPU & HPC Workloads: Familiarity with GPU workloads, batch jobs, training pipelines, inference workloads, or HPC-style compute environments
• Cross-Layer Debugging: Proven ability to debug infrastructure issues across application, network, storage, compute, and orchestration layers
• Security & Reliability Instincts: Strong instincts for isolation, RBAC, uptime, and traceability on workloads that touch customers
• High Agency: You navigate ambiguity without waiting for permission, with a bias toward simple, composable infrastructure that serves real customer workflows over scheduling another meeting
• Communication: Strong written and verbal communication. You can hold your own in a technical conversation with a customer CTO and debrief a design partner engagement to the Head of Physical AI

Benefits

• Health Insurance: 100% company-paid medical, dental, and vision coverage for employees and families
• 401(k) Plan: Up to 4% company match with immediate vesting
• Parental Leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers
• Remote Work Reimbursement: Up to $85/month for mobile and internet
• Disability & Life Insurance: Company-paid short-term, long-term, and life insurance coverage