Software Engineer - Distributed Systems

Software Engineer - Distributed SystemsWe're working with a well-funded Series A company building a new class of cloud infrastructure for AI. They're tackling a fundamental problem: today's AI systems are tightly coupled to specific hardware, creating limits in cost, scale, and efficiency.Their approach decouples workloads from hardware — dynamically partitioning and scheduling them across heterogeneous compute (GPUs, accelerators, multi-gen systems). This is deep, production-grade distributed systems work operating at real scale.What you'll doOwn core distributed systems from design ? build ? deployment ? operationDesign scheduling, routing, and resource management systems across thousands of nodesBuild production-grade control planes and APIs for workload orchestrationMake explicit tradeoffs around performance, reliability, and efficiency at scaleDebug complex distributed failures and continuously improve system behaviourWhat makes this interestingHigh ownership: you're building foundational infrastructure, not abstracted layersReal scale: systems designed for large, multi-cluster / datacenter environmentsHard problems: concurrency, scheduling, failure modes, and resource allocationHeterogeneous compute: working beyond standard cloud abstractionsEarly-stage: opportunity to shape architecture with real production constraintsWe're looking forEngineers who have built or operated distributed systems in productionStrong fundamentals in concurrency, systems design, and failure handlingEvidence of ownership over meaningful systems (not just contributions)Comfort reasoning about tradeoffs in large-scale environmentsAbility to clearly explain design decisions and system behaviourIt's not necessary, but it's great if you have:Experience with Kubernetes or similar systems beyond basic usageBackground in scheduling, queues, or resource management systemsExperience designing service-oriented architectures (RPC, async systems)Systems-level programming experience (e.g. Go, C++, Python)