Software Developer 4

In this role you will lead the design and development team to build advanced AI applications powered by AI models. You will use AI/ML to automate, optimize, and secure networks, focusing on tasks like self-provisioning, auto-ingesting, auto-qualifying systems and self-healing networks, requiring skills in Python, ML frameworks, training AI models, and an understanding of networking protocols, data center designs, infrastructure as a service, network monitoring and network automation.

As a Principal AI Developer in the Networking Org, you will be responsible for building and optimizing large-scale AI systems, ensuring scalability, reliability, and performance.

The candidate should be able to work collaboratively with cross-functional teams to drive the development and deployment of AI solutions.

If you have a passion for building cutting-edge AI applications and are looking for a challenging role, we encourage you to apply.

Strong problem-solving skills, attention to detail, and excellent communication skills are essential for this role.

• Design and implement scalable orchestration for serving and training AI/ML models.
• Explore and incorporate contemporary research on AI, agents, and inference systems into the software stack for designing, monitoring, troubleshooting and deploying networks.
• Evaluate, Integrate, and Optimize technologies across the stack, for latency, throughput, and resource utilization for training and inference workloads.
• Lead initiatives in AI systems design, including Retrieval-Augmented Generation (RAG) and LLM fine-tuning.
• Design and develop scalable services and tools to support GPU-accelerated AI pipelines, Python/Go, and observability frameworks.

Required/Preferred experience:

• Strong Python and ML frameworks (PyTorch, TensorFlow)
• LLMs, embeddings, vector search, RAG pipelines, and fine-tuning
• Data engineering: Spark, Kafka, Flink, OCI Streaming/Data Flow
• Distributed systems and large-scale training/inference
• Handling network telemetry (NetFlow, packet captures, streaming telemetry)
• Network automation frameworks (Terraform, Ansible, NAPALM, Batfish is a plus)
• Containerization, model serving, GPU workflows, CI/CD, and MLOps tools