Full-Time

Senior Solutions Architect

GenAI Agentic Networks, Telco

Updated on 7/21/2026

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI HPC platforms

Compensation Overview

$184k - $356.5k/yr

+ Equity

Company Historically Provides H1B Sponsorship

Remote in USA + 6 more

More locations: Seattle, WA, USA | Washington, USA | Texas, USA | Jackson Township, NJ, USA | Santa Clara, CA, USA | Colorado, USA

Remote

Remote-friendly; up to 40% travel for on-site engagements.

Category
Sales & Solution Engineering (1)
Required Skills
Python
NoSQL
Neural Networks
Pytorch
Apache Spark
SQL
ETL
RAG
Pandas
Elasticsearch
LangChain
C/C++

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Requirements
  • MSc or PhD in Computer Science, Electrical Engineering, Software Engineering, or a related field—or equivalent experience building real systems—with 6+ years developing and deploying AI/ML systems at scale
  • Hands-on experience building enterprise Retrieval-Augmented Generation (RAG) systems with open-source models (Llama, Llama-based like LLaMA, Mistral, or similar) and orchestration frameworks like LangChain or LlamaIndex, paired with solid deep learning fundamentals
  • Proficiency in Python, solid understanding of C++, and experience with PyTorch or a comparable deep learning framework
  • Real familiarity with telecommunications network data—telemetry, logs, SNMP, NetFlow/IPFIX, and time-series streams—paired with hands-on experience across SQL, NoSQL, Elasticsearch, Apache Spark, and Pandas
  • The communication skills to talk technical trade-offs with engineers and outcomes with business partners — often in the same conversation
Responsibilities
  • Designing, building, and continuously improving agentic LLM applications targeting Telco Network Operations and Autonomous Networks—covering orchestration, tool use, memory, and multi-agent coordination patterns—while evaluating and applying the latest advances in model fine-tuning and customization for telecom-specific corpora including network telemetry, logs, SNMP, NetFlow/IPFIX, and streaming time-series data
  • Enable NVIDIA strategic Telco partners to build enterprise AI solutions on the NVIDIA accelerated computing stack, including NIMs and NeMo microservices
  • Provide deep technical guidance to developers onboarding to NVIDIA AI platforms and SDKs; serve as the primary technical partner and customer point of contact for integration challenges
  • Anticipate partner and customer needs across the adoption lifecycle, identify enablement opportunities that accelerate GenAI utilization, and translate those insights into reference architectures for Agentic AI in Telco—documenting design trade-offs, standard practices, and failure modes, then feeding findings systematically back to product and engineering
  • Advise on high-performance ETL pipeline design for telecom data: scalable, real-time ingestion workflows using NVIDIA Data Acceleration SDKs (RAPIDS, Morpheus) for high-volume telemetry and event streams
Desired Qualifications
  • Experience with NVIDIA AI Enterprise software: Morpheus, RAPIDS, NeMo, and NIM
  • Agentic framework fluency: LangGraph, AutoGen, NVIDIA Colang 2.0, or similar multi-agent tools
  • 5G / 6G and O-RAN depth: Next-generation Telco architecture spanning 5GC, Open RAN, network slicing, MEC, and 3GPP standards (Rel. 15–18), combined with O-RAN automation including xApps, rApps, RIC, SDN/NFV, and protocols such as NETCONF, gNMI, and RESTCONF
  • MLOps and DevOps: Kubernetes, Docker, Helm, Jupyter-based automation pipelines
  • Infrastructure awareness around NVIDIA InfiniBand or high-speed Ethernet for distributed model serving

NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify Jobs

Simplify's Take

What believers are saying

  • Rubin delivers 5x faster inference and 3.5x faster training than Blackwell starting H2 2026.
  • Major hyperscalers Microsoft, AWS, Google Cloud, and CoreWe confirmed Vera Rubin implementation ahead of Q3 2026.
  • Rubin Ultra targets 15 ExaFLOPS FP4 inference with 1.5 PB/s NVLink bandwidth per rack in 2027.

What critics are saying

  • HBM4 scarcity from SK Hynix and Micron forces Rubin production cut to 1.5M units in 2026.
  • Kyber NVL144 rack delayed to 2028 due to TSMC 78-layer PCB yield failure, breaking annual cadence.
  • Rubin Ultra cuts HBM4E stacks to 12-Hi, delivering only 2.66x instead of 4x performance gain.

What makes NVIDIA unique

  • Vera Rubin is a six-chip extreme codesigned AI supercomputer platform, not just a GPU.
  • NVIDIA shifted to annual architecture cadence with Rubin, Ultra, and Feynman releases through 2028.
  • Vera CPU with 88 ARM cores enables per-GPU efficiency and 1/10 Blackwell operational costs.

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Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

1%

1 year growth

-1%

2 year growth

-1%
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