Software Engineer, Distributed Systems

About this role:

You are an experienced software engineer who is passionate about building large-scale computing platforms. You have experience building systems that remain reliable under high traffic, partial failures, and changing capacity. You know how to deliver reliability, performance, and scale with minimum operational load.

What you'll do:

• Take ownership of one or more of the Rust/Python systems that power our AI inference and large-scale GPU computing platform

• Design for 100x growth in workloads and GPU capacity, with reliable, low-latency execution across the globe

• Use AI aggressively to accelerate development and automate repetitive operations, alerting, and recovery

You will specialize in one or more of these critical areas:

• Request routing and queuing on a global scale

• App deployment and autoscaling

• Worker orchestration and placement

• GPU fleet autoscaling and capacity management

• GPU fleet lifecycle automation: provisioning, diagnostics & recovery, upgrades, tracking

• Global file storage, caching and distribution

• Global IP backbone: private networking across datacenters, elastic public IPs, ACLs/firewalls, private connectivity

• Workload execution: containerization, globally distributed filesystems, RAM/VRAM snapshotting

Qualifications/Nice to have:

• 3+ years building and operating large-scale production systems, with a track record of reliability and scale

• Strong Rust and/or Python skills

• Strong systems fundamentals, with technical depth relevant to your specialization: distributed coordination, scheduling, fault tolerance, Linux, networking, storage, or capacity management

• Experience building and using observability to drive performance and reliability decisions

• Clear communication, sound technical judgment, and the initiative to move quickly, drive decisions across teams, and own systems from design through production

• Multi-tenant compute platforms, AI inference or training infrastructure, GPU workload scheduling

• High-performance systems programming: async runtimes, zero-copy, memory-safe concurrency

• Linux systems engineering and fleet automation: configuration management, kernel and driver debugging, safe upgrades, and automated recovery

• Distributed filesystems like JuiceFS and Lustre

• Experience with Nvidia/AMD GPU infrastructure; DCGM, NVLink, RDMA, InfiniBand/RoCEv2

• Global networking and routing: BGP, ECMP, tunnels, eBPF, Geneve

What we offer at fal:

• Interesting and challenging work

• A lot of learning and growth opportunities

• Regular team events and offsites

U.S. EQUAL EMPLOYMENT OPPORTUNITY INFORMATION:

fal provides equal employment opportunities to applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other classification protected by applicable law.