Senior Software Architect, AI Networking

Responsibilities

• Design and evolve scalable architectures for multi-node LLM inference across GPU clusters.
• Develop infrastructure to optimize latency, throughput, and cost-efficiency of serving large models in production.
• Collaborate with model, systems, compiler, and networking teams to ensure complete, high-performance solutions.
• Prototype novel approaches to KV cache handling, tensor/pipeline parallel execution, and dynamic batching.
• Evaluate and integrate new software and hardware technologies relevant to Core Spectrum-X technologies, such as load balancing, telemetry, congestion control, vertical application integration.
• Work closely with internal teams and external partners to translate high-level architecture into reliable, high-performance systems.
• Author design documents, internal specs, and technical blog posts and contribute to open-source efforts when appropriate.
• What We Need to See
• Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, or equivalent experience.
• 8+ years of experience building large-scale distributed systems or performance-critical software.

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