Agentic AI Software Engineer Palo Alto

As an Agentic AI Software Engineer, you will own the design and development of intelligent systems that reason over real-time network telemetry, automate operational decisions, and surface actionable insights to cluster operators. You will integrate frontier LLM APIs alongside purpose-trained smaller models fine-tuned for networking-specific tasks to enable autonomous network management. You will solve hard problems at the intersection of LLM orchestration, retrieval-augmented generation, and low-latency infrastructure. This role spans architecture through production deployment across Aria’s cluster software stack. Responsibilities Design and build agentic workflows like tool use, multi-step reasoning, and RAG pipelines that operate over fine-grained GPU-cluster network telemetry Integrate LLM APIs (OpenAI, Anthropic, Google or equivalent) into production systems with reliable orchestration, structured outputs, and robust failure handling Fine-tune and distill smaller task-specific models (LoRA, PEFT, or equivalent) for networking-domain tasks including anomaly detection, fault classification, and predictive analytics Architect the AI layer of Aria Cluster Software, defining how agentic components interact with the telemetry pipeline, control plane, and operator-facing interfaces Define evaluation frameworks to measure AI system accuracy, latency, and decision quality against real network operational outcomes Partner with telemetry and backend engineers to shape data schemas and streaming infrastructure that serve AI workloads efficiently Ship AI capabilities end to end with appropriate observability, rollback mechanisms, and confidence calibration Qualifications Bachelor’s degree (or foreign equivalent) in Computer Science, Software Engineering, Computer Engineering, or a closely related technical field Minimum 5 years of software engineering experience, with at least 2 years in hands-on AI/ML product development Experience designing and implementing agentic workflows including multi-step reasoning, retrieval-augmented generation, and dynamic tool invocation Experience fine-tuning or training smaller models using LoRA, PEFT, distillation, or equivalent techniques Working knowledge of ML frameworks such as PyTorch, JAX, Tensorflow, etc. Experience building AI-powered control or automation systems that act on live system state is preferred Experience applying AI/ML to networking, infrastructure, or observability domains is a significant plus #J-18808-Ljbffr Aria Networks, Inc.