Principal Software Engineer - AI ADC

A10 Networks, IncSan Jose, CA
$0 - $230,000Hybrid

About The Position

A10 Networks is accelerating its AI‑driven innovation across the ADC and GSLB product lines. We are seeking a highly experienced Sr. Staff Engineer to be part of the development of next‑generation AI‑aware traffic management and AI Gateway capabilities. This role combines deep domain expertise in Application Delivery Controllers (ADC), Server Load Balancing (SLB), DNS/GSLB, with practical experience in AI/LLM systems, to build intelligent routing, inference‑aware load balancing, and Layer‑8 contextual decision engines for AI workloads. The ideal candidate is a senior staff engineer who can drive architecture, design, prototyping, and execution—working closely with product management, platform teams, and AI strategy groups.

Requirements

  • Deep domain expertise in Application Delivery Controllers (ADC), Server Load Balancing (SLB), DNS/GSLB
  • Practical experience in AI/LLM systems
  • Ability to drive architecture, design, prototyping, and execution
  • Experience working closely with product management, platform teams, and AI strategy groups

Responsibilities

  • Lead architecture and development of AI Gateway components for intelligent routing of LLM/AI application traffic
  • Design and implement LLM‑aware load balancing, incorporating semantic, token, latency, and model‑level insights into traffic decisions
  • Develop enhancements for ADC and GSLB platforms to support AI workloads, including: Token‑aware rate limiting, Inference latency‑based routing, AI model endpoint discovery and health checks, Integration with vector databases, model registries, and ML observability systems
  • Contribute to advanced features including Layer‑8 context‑aware routing, adaptive traffic shaping, and AI‑driven anomaly detection
  • Drive system‑wide architecture: data plane, control plane, configuration, and distributed state management
  • Mentor engineering teams on AI workload behaviors, traffic characteristics, and tuning strategies
  • Collaborate with AI research and platform teams to align architectural decisions with product roadmap.
  • Create guidance on performance optimization, benchmarking, and scaling for global multi‑node deployments
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