Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

Tailor your resume to this Software Engineer – Cloud Infrastructure role.

Rezi rewrites your resume against FriendliAI's job description. Free.

Resume score gauge reading 58 out of 100

Don't guess if your resume is good enough.

See how it scores against the Software Engineer – Cloud Infrastructure posting at FriendliAI — free, in seconds.

About the Role

FriendliAI is seeking a Cloud Infrastructure Engineer to lead the architecture and development of their GPU-accelerated AI inference cloud platform. This role involves designing cluster architecture, extending Kubernetes, and managing the network infrastructure critical for inference traffic.

Responsibilities

Own the architecture of the multi-cluster, multi-tenant Kubernetes fleet, including cluster topology, control plane, and etcd lifecycle.
Extend Kubernetes using custom controllers, operators, and CRDs.
Design GPU scheduling and capacity strategy, encompassing topology-aware placement, node pools, priority, preemption, and tenant quotas.
Build autoscaling solutions for inference traffic, including queue-driven pod scaling, node autoscaling, scale-to-zero, and cold-start reduction.
Own the Kubernetes network data plane, including CNI, IPAM, DNS, ingress, and L4/L7 load balancing.
Design cross-AZ, cross-region, and cross-cluster connectivity, and operate the service mesh for routing, mTLS, and traffic policy.
Debug and resolve production network issues, driving permanent fixes.
Define SLOs for platform-critical systems and lead post-incident hardening.
Deliver infrastructure as code using Terraform, Helm, and GitOps.
Collaborate with inference engine, platform, SRE, and security teams to translate serving requirements into platform capabilities.

Requirements

5+ years of experience designing, building, and operating large-scale Kubernetes infrastructure in production.
Proven experience operating large-scale, high-traffic network services in production.
Deep understanding of Kubernetes internals (API server, scheduler, controller loops, kubelet, etcd).
Strong command of Kubernetes and cloud networking (CNI, kube-proxy/eBPF datapaths, DNS, load balancing, service mesh, VPC routing).
Proficiency with AWS, Terraform, Helm, and Ansible.
Programming skills in Go or Python for building infrastructure tooling and automation.
Strong debugging skills across distributed systems, containers, and the Linux networking stack.
Clear written and verbal communication skills, including the ability to document architectural decisions.

Skills

Kubernetes
Cloud Networking
CNI
Kube-proxy/eBPF
DNS
Load Balancing
Service Mesh
VPC Routing
AWS
Terraform
Helm
Ansible
Go
Python
Distributed Systems Debugging
Container Debugging
Linux Networking Stack Debugging
Cilium
eBPF
Kubespray
NVIDIA GPU Operator
RDMA/RoCE
InfiniBand
EFA
SR-IOV
NCCL Tuning

Location

Remote

Work Type

Full-time

Experience Level

5+ years

Education Level

Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent.

Benefits

Flexible working hours
Daily lunch and dinner provided
Unlimited snacks and beverages
Supportive and highly collaborative work environment
Health check-up support
Top-tier equipment/hardware support
Competitive compensation
Startup equity
Health insurance

About the Company

FriendliAI is building the fastest inference cloud for agents, designed to run frontier open-weight models at scale.
The platform offers significantly faster output token speed, lower inference costs, and high uptime for demanding agent workloads.
It is a fast-moving team focused on generative AI infrastructure.
FriendliAI aims to provide a reliable platform for AI inference.