LLM AIOps Development Engineer

Responsibilities

• Develop a real-time network observability platform using telemetry from gNMI, NETCONF, IPFIX/NetFlow, and SNMP.
• Build machine-learning and deep-learning systems for anomaly detection, correlation analysis, noise reduction, and root-cause analysis across network and application layers.
• Develop RAG-powered conversational operations assistants that query knowledge bases and monitoring data.
• Build operational agents that generate, recommend, and execute controlled remediation plans and runbooks through network tools and APIs.
• Create network capacity, risk, and device-health prediction capabilities using historical data and business-growth models.
• Design highly available and scalable systems spanning data collection, model training, online inference, and closed-loop actions.

Requirements

• Deep understanding of data-center network architectures such as Spine-Leaf Fabric and protocols including EVPN/VXLAN and BGP/OSPF.
• In-depth knowledge of the Linux network stack.
• Strong software-engineering and system-design skills with mastery of Go or Python.
• Experience with modern development workflows, microservices, containerization, Docker, Kubernetes, and CI/CD.
• Experience in one or more of big-data processing, real-time data pipelines, analytics systems, observability platforms, graph databases, alert platforms, or event platforms.
• Interest or hands-on experience in LLM and agent applications for operations, including RAG, tool use, and safety evaluation.
• Preferred: experience with hyperscale data-center networks, LLM/agent intelligent-operations projects, relevant open-source communities, high-performance networking, SmartNICs, DPDK/eBPF, or network configuration and control systems.