Solutions Architect, GenAI Agentic Networks - Telco

NVIDIA is looking for an ambitious and forward-thinking solution architect to help in the development of Agentic AI applications which will be used to automate Telco Network Operations using the latest Generative AI models and research, including NLP, RAG, distributed computing and large-scale system design. In this role, become the trusted technical authority on Generative AI frameworks and have deep knowledge of Telco Networks Data.

As part of the Telco Solution Architecture team, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Join the team and see how you can make a lasting impact on the world by applying Agentic AI to automate real enterprise problems.

What you will be doing:

• Building agentic LLM applications and exploring the latest advancements in model training, fine-tuning and customization for Telco Networks Data.

• Enabling NVIDIA strategic Telecommunications partners to create enterprise AI solutions using accelerated computing stack including NIMs and NeMo microservices.

• Collaborate with developers and onboard them to NVIDIA AI platforms and SDKs by providing deep technical guidance.

• Anticipate Telecommunication partners and customers needs and find enablement opportunities to expand adoption and utilization of NVIDIA Generative AI products and platforms.

• Establish and build repeatable reference architectures for Agentic AI, communicating standard processes and understanding solution trade-offs. Share findings and feedback to enhance products and services.

• Help customers design high-performance ETL pipelines for telecom networks: Advise on building efficient, scalable workflows using NVIDIA Data Acceleration SDKs to process high-volume, real-time network data from sources like telemetry, logs, streaming data, SNMP, and NetFlow/IPFIX.

What we need to see:

• MSc, PhD in Computer Science, Electrical Engineering, Software Engineer, ML Engineer, or related fields (or equivalent experience).

• 5+ years of relevant work experience in developing and deploying AI models at scale as a Software Engineer or deep learning engineer.

• Proven track record of building enterprise-grade RAG based systems using open-source models and orchestration frameworks with strong foundation in deep learning, with a particular emphasis on generative models.

• Proficiency in Python, C++ programming and Deep Learning frameworks.

• Expertise in Telecom Network Data: Strong knowledge of network telemetry, logs, SNMP, NetFlow/IPFIX, streaming data, and time-series data processing.

• Experience with Data Extraction & Processing Tools: Familiarity with SQL, NoSQL, Elasticsearch, Apache Spark, Pandas, and AI-based feature engineering.

• Excellent communication and presentation skills to effectively collaborate with both internal and external customers.

Ways to stand out from the crowd:

• Hands-on experience with …