Customer-Facing AI Inference Engineer (Kubernetes & Scale)

FriendliAI Inc.; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive compensation

Lunch and dinner provided

Health check‑up and hardware support

Flexible working hours

Job summary

FriendliAI is seeking a Forward Deployed Engineer to help enterprises deploy, scale, and operate generative AI workloads on FriendliAI infrastructure. You will work directly with customers to implement production‑grade applications using our products like Serverless Endpoints, Dedicated Endpoints, or Container.

You will collaborate with customers to solve AI inference challenges, including scaling, orchestration, and monitoring, in a hands-on, customer-embedded role.

Qualifications

• 3+ years of experience in cloud infrastructure, DevOps, or reliability engineering.
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent.
• Proficiency with Kubernetes, Docker, Terraform, and Helm.

Responsibilities

• Design and implement large-scale deployment architectures for LLM and multimodal inference.
• Deploy and manage containerized workloads across Kubernetes clusters.
• Diagnose production issues and implement temporary fixes as needed.
• Collaborate with customers’ DevOps teams to integrate FriendliAI’s infrastructure into their CI/CD workflows.
• Develop scripts, Helm charts, and Terraform modules to simplify repeated deployments.
• Contribute field insights to shape platform reliability, observability, and scaling strategies.
• Lead workshops, technical sessions, or webinars to help customers master infrastructure best practices.

Skills

Cloud infrastructure

Distributed systems

Problem solving

Backend tooling

AI tooling

Education

Bachelor’s or Master’s in CS/CE/EE

Tools

Kubernetes

Docker

Terraform

Helm

Job description

FriendliAI is seeking a Forward Deployed Engineer to help enterprises deploy, scale, and operate generative AI workloads on FriendliAI infrastructure. You will work directly with customers to implement production‑grade applications using our products like Serverless Endpoints, Dedicated Endpoints, or Container.

You will collaborate with customers to solve AI inference challenges, including scaling, orchestration, and monitoring, in a hands-on, customer-embedded role.