Senior Solutions Architect, Retail

Nvidia

Remote

Quick summary

Work type: Remote
Location: Canada
Salary: $184,000–$287,500 / yr
Posted: 46 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $188k

This role $236k

$129k most similar roles pay here $304k

This role pays more than 86% of similar roles. Most pay $151,505–$224,650 — the shaded band above. At the midpoint, this role pays about $236k versus about $188k for comparable roles.

Based on 240 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 985 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 971 roles with salary data.

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View all roles at Nvidia

At a glance

TL;DR · Senior Solutions Architect, Retail

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As a Solutions Architect at NVIDIA, you will join the cutting-edge Agentic AI team to drive the development of sophisticated enterprise solutions for leading Retail, CPG, and QSR companies. Your role involves building complex agentic systems with multi-agent coordination and advanced planning frameworks, developing high-performance retrieval pipelines (RAG), and optimizing inference performance using GPU-accelerated NVIDIA technologies like NIM, NeMo Framework, Dynamo, and the NeMo Agent Toolkit. You will also collaborate on PoCs, reference architectures, and technical workshops to empower partner engineering teams and scale global expertise through reusable assets and documentation. This role requires a strong background in deep learning, Python programming, and experience with frameworks such as PyTorch, TensorFlow, LangGraph, LlamaIndex, and OpenAI Agents SDK.

Skills

Python PyTorch TensorFlow NVIDIA NIM NeMo Framework LangChain LlamaIndex CrewAI OpenAI Agents SDK Docker Linux CUDA SFT LoRA DPO PPO GRPO DAPO RLVF Prometheus Grafana

What you'll do

Build complex agentic systems featuring multi-agent coordination and advanced planning frameworks.
Develop full-scale solutions including high-performance retrieval pipelines spanning various data sources.
Optimize inference performance using GPU-accelerated frameworks and NVIDIA’s AI infrastructure stack.
Create PoCs and reference architectures for production-grade generative AI pipelines.
Integrate NVIDIA software into native platforms to accelerate deployment of production workloads.
Empower partner engineering teams through technical workshops and deep-dive architecture reviews.

What we're looking for

8+ years of experience in deep learning, machine learning, or distributed AI systems.
Strong programming skills in Python, C/C++, and Linux environments.
Hands-on experience building LLM and generative AI applications.
Experience with agentic or multi-agent AI systems using relevant frameworks.
Proficiency in NVIDIA GPUs and AI software like NIM, NeMo Framework, and NeMo Agent Toolkit.
Background in optimizing reasoning-focused LLMs through engineering techniques.
Ability to rapidly prototype AI applications and build scalable GPU-accelerated architectures.

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