> Markdown version of [/jobs/ext/4657468-software-engineer-distributed-systems](https://www.wearedevelopers.com/jobs/ext/4657468-software-engineer-distributed-systems). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer, Distributed Systems - **Company:** Fal - Features & Labels, Inc. - **Location:** San Francisco, CA, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Computing Platforms, Border Gateway Protocol, Configuration Management, Software Debugging, Linux, File Systems, Distributed Systems, Fault Tolerance, General-Purpose Computing on Graphics Processing Units, InfiniBand, Python (Programming Language), Routing, Remote Direct Memory Access, Software Engineering, System Programming, Scripting, Graphics Processing Unit (GPU), Autoscaling, Concurrency, Caching, Information Technology, Hardware Infrastructure, Model Inference - **Published:** November 10, 2026 - **Apply:** https://www.careerbuilder.com/job-details/software-engineer-distributed-systems-san-francisco-ca--083c2955-fb08-41a7-8282-f738f076ef41 ## About the Role Software Engineering, Distributed Computing, Ecosystems, Artificial Intelligence (AI), Entertainment and Media, Computer Systems, Building Systems, Software Engineering, Python Programming/Scripting Language, GPU (Graphics Processing Unit), 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., * 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 ## Description * 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, * 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