Description
Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers.
In the world of distributed AI training and inference, raw GPU and CPU horsepower is just a part of the story. High-performance networking and storage are the critical components that enable and unite these systems, making groundbreaking AI training and inference possible.
We're looking for an experienced Senior Software Engineer to join our storage team. You'll join a team responsible for developing and implementing our next-generation storage software. This role requires expertise in distributed systems, and an in-depth understanding of file, block, and object storage protocols.
Responsibilities:
- Design and build a vendor-agnostic control plane that provisions, scales, heals, and meters storage across the platforms our customers actually demand.
- Define the internal abstraction layer that hides vendor-specific APIs, failure semantics, QoS knobs, and telemetry formats behind one declarative interface.
- Build reconciliation-loop and CRD-based orchestration that manages capacity, tenancy, encryption domains, and placement across data centers and availability zones.
- Own multi-tenant isolation end to end: namespace and subsystem partitioning, per-tenant QoS and rate limiting, credential and key lifecycle, blast-radius containment, noisy-neighbor detection.
- Design the capacity and placement engine: PCIe-topology-aware, NUMA-aware, failure-domain-aware.
- Instrument everything: SLI/SLO definitions, fleet-wide performance regression detection, and the observability pipeline that makes a petabyte fleet debuggable.
Requirements:
- Bachelor's or Master's degree in Computer Science or a related field.
- 5+ years of experience in software development for storage systems.
- Proven experience with distributed systems programming and concepts.
- Strong programming skills in languages such as C, C++, Go, or Python.
- Experience with Linux kernel internals and system-level programming.
- Experience with one or more storage protocols and file systems.
- Familiarity with containerization technologies like Docker and Kubernetes.
Nice to Have:
- Experience with AI/ML workloads and the unique storage challenges they present.
- Knowledge of data center networking and high-speed interconnects.
- Experience with performance tuning and optimization of storage systems.
- Familiarity with hardware acceleration technologies, specifically GPUs and DPUs.
Benefits:
- Generous cash & equity compensation
- Health, dental, and vision coverage for you and your dependents
- Wellness and commuter stipends for select roles
- 401k Plan with 2% company match (USA employees)
- Flexible paid time off plan
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