Senior Solutions Architect, Generative AI Deployment and AIOps

Nvidia

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Remote
Salary: $184,000–$287,500 / yr
Posted: 14 days ago
Freshness: Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $199k

This role $236k

$138k most similar roles pay here $304k

This role pays more than 77% of similar roles. Most pay $162,000–$235,750 — the shaded band above. At the midpoint, this role pays about $236k versus about $199k for comparable roles.

Based on 239 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · Senior Solutions Architect, Generative AI Deployment and AIOps

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As a Senior Solutions Architect, Generative AI Deployment and AIOps, you will serve as a trusted technical advisor to customers building solutions with advanced AI technology. You will work within an interdisciplinary team to develop proof-of-concepts focused on inference for Generative AI and Large Language Models while collaborating with internal engineering and product teams on performance analysis and modeling of inference software. Your daily responsibilities include partnering with developers, researchers, and data scientists to define high-value solutions and analyzing the power efficiency of AI inference workloads on Kubernetes. You will utilize PyTorch, TensorFlow, Python, C++, and NVIDIA libraries like TensorRT-LLM and NIM. The role addresses technical challenges in GPU orchestration, Multi-Instance GPU management, and MLOps for large-scale deep learning deployments across various industries using accelerated computing platforms.

What does a Solutions Architect earn in Remote?

Median $231100 from 71 postings across 13 companies.

See salary data

Skills

Generative AI LLMs Deep Learning PyTorch TensorFlow Python C++ Kubernetes MLOps NVIDIA NIM TensorRT TensorRT-LLM GPU Orchestration Multi-Instance GPU (MIG) Distributed Computing Performance Analysis Profiling

What you'll do

Act as a trusted technical advisor to customers building solutions with Generative AI and Large Language Models.
Develop proof-of-concepts focused on inference for Generative AI and LLMs.
Define high-value solutions based on the specific strategies and technical needs of customers.
Guide customers in adopting and building creative solutions using NVIDIA technology and MLOps tools.
Analyze performance and power efficiency of AI inference workloads running on Kubernetes.
Partner with internal engineering, product, and business teams to perform modeling of inference software.
Engage with developers, researchers, and data scientists to address diverse technical requirements.
Collaborate with lighthouse customers and industry partners to promote NVIDIA's computing platforms.

What we're looking for

BS, MS, or PhD in Computer Science, Engineering, Physics, Mathematics, or a related field (or equivalent experience).
8+ years of hands-on experience with Deep Learning frameworks such as PyTorch and TensorFlow.
Strong fundamentals in programming, optimizations, and software design, specifically in Python.
Proficiency in problem-solving and debugging for GPU orchestration and Multi-Instance GPU management within Kubernetes.
Experience with containerization, orchestration technologies, and monitoring/observability solutions for AI deployments.
Excellent knowledge of the theory and practice of LLM and Deep Learning inference.
Strong presentation, communication, and collaboration skills.
Experience with NVIDIA GPUs and software libraries such as NVIDIA NIM, Dynamo, TensorRT, and TensorRT-LLM.

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