Senior Solutions Architect, GenAI Agentic Networks

What you'll do

• Design and deploy agentic LLM applications for telecommunications network operations and autonomous networks.
• Evaluate and apply model fine-tuning for telecom-specific data like network telemetry, logs, and time-series streams.
• Guide strategic partners in building enterprise AI solutions using NVIDIA’s accelerated computing stack and microservices.
• Provide technical guidance to developers on onboarding to NVIDIA AI platforms and resolving integration challenges.
• Create reference architectures for Agentic AI in Telco, documenting design trade-offs and standard practices.
• Advise on high-performance ETL pipeline designs for real-time ingestion of high-volume telecom telemetry.
• Translate customer needs into systematic feedback for product and engineering teams to improve AI offerings.

What we're looking for

• MSc or PhD in Computer Science, Electrical Engineering, Software Engineering, or a related field, or equivalent experience building real systems.
• 6+ years of experience developing and deploying AI/ML systems at scale.
• Hands-on experience building enterprise RAG systems with open-source models and orchestration frameworks like LangChain or LlamaIndex.
• Proficiency in Python, a solid understanding of C++, and experience with PyTorch or a comparable deep learning framework.
• Familiarity with Telco network data (telemetry, logs, SNMP, NetFlow/IPFIX) and experience with SQL, NoSQL, Elasticsearch, Apache Spark, and Pandas.
• Ability to communicate technical trade-offs with engineers and business outcomes with partners.
• Experience with NVIDIA AI Enterprise software including Morpheus, RAPIDS, NeMo, and NIM (preferred).
• Fluency in agentic frameworks like LangGraph, AutoGen, or NVIDIA Colang 2.0 (preferred).