{"id":117877,"url":"https://alion.io/job/fal-software-engineer-distributed-systems","title":"Software Engineer, Distributed Systems","company":{"id":44380,"name":"Fal","domain":"fal.ai","url":"https://alion.io/company/fal","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":87,"open_postings":22,"ghost_share":0,"stale_share":0.318,"repost_share":0,"time_to_fill_p50_days":65,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Backend","role_family":"Backend","seniority":"middle","employment_type":"full_time","work_mode":"remote","remote_scope":"worldwide","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":180000,"max":250000,"currency":"USD","period":"year","gross":null,"usd_annual":250000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Linux","optional":false},{"name":"Python","optional":false},{"name":"Rust","optional":false},{"name":"BGP","optional":true},{"name":"eBPF","optional":true},{"name":"InfiniBand","optional":true},{"name":"NVLink","optional":true}],"status":"live","first_seen_at":"2026-03-13T20:15:21Z","employer_posted_date":"2026-03-13","last_verified_at":"2026-10-17T11:17:53Z","board_verified":true,"closed_at":null,"days_open":217,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":217},"description":"fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products.\nAs generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on.\nAbout this role:\nYou 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.\nWhat you'll do:\nTake ownership of one or more of the Rust/Python systems that power our AI inference and large-scale GPU computing platform\n\nDesign for 100x growth in workloads and GPU capacity, with reliable, low-latency execution across the globe\n\nUse AI aggressively to accelerate development and automate repetitive operations, alerting, and recovery\n\nYou will specialize in one or more of these critical areas:\nRequest routing and queuing on a global scale\n\nApp deployment and autoscaling\n\nWorker orchestration and placement\n\nGPU fleet autoscaling and capacity management\n\nGPU fleet lifecycle automation: provisioning, diagnostics & recovery, upgrades, tracking\n\nGlobal file storage, caching and distribution\n\nGlobal IP backbone: private networking across datacenters, elastic public IPs, ACLs/firewalls, private connectivity\n\nWorkload execution: containerization, globally distributed filesystems, RAM/VRAM snapshotting\n\nQualifications:\n3+ years building and operating large-scale production systems, with a track record of reliability and scale\n\nStrong Rust and/or Python skills\n\nStrong systems fundamentals, with technical depth relevant to your specialization: distributed coordination, scheduling, fault tolerance, Linux, networking, storage, or capacity management\n\nExperience building and using observability to drive performance and reliability decisions\n\nClear communication, sound technical judgment, and the initiative to move quickly, drive decisions across teams, and own systems from design through production\n\nNice to have:\nMulti-tenant compute platforms, AI inference or training infrastructure, GPU workload scheduling\n\nHigh-performance systems programming: async runtimes, zero-copy, memory-safe concurrency\n\nLinux systems engineering and fleet automation: configuration management, kernel and driver debugging, safe upgrades, and automated recovery\n\nDistributed filesystems like JuiceFS and Lustre\n\nExperience with Nvidia/AMD GPU infrastructure; 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