Agentic AI Software Engineer Palo Alto

Aria Networks, Inc.; Palo Alto, Northern (CA, KY); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Aria Networks, Inc. is seeking an Agentic AI Software Engineer to own the design of intelligent systems that reason over real-time network telemetry and automate operational decisions across Aria’s cluster software stack.

You will integrate frontier LLM APIs with fine-tuned models for networking tasks, build end-to-end AI workflows, and partner with telemetry and backend engineers to deliver observable, low-latency solutions.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or a closely related 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.

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

Skills

Agentic workflows design

AI/ML product development

LLM API integration

Networking-domain AI apps

Education

Bachelor’s degree in CS/EE/related

Tools

PyTorch

JAX

TensorFlow

Job description

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