Full-Time

Senior Architect

AI Solutions Engineering

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI HPC platforms

Compensation Overview

$224k - $431.3k/yr

+ Equity

Company Historically Provides H1B Sponsorship

Santa Clara, CA, USA

In Person

Category
Sales & Solution Engineering (1)
Required Skills
LLM
Chef
Bash
Kubernetes
Python
Puppet
MySQL
Git
Apache Kafka
Java
Docker
RAG
JFrog
Elasticsearch
MongoDB
REST APIs
Hadoop
LangChain
Cassandra
Requirements
  • BS Electrical Engineering or Computer Science or equivalent experience with 12+ years of systems software development with at least 1 year of experience in developing/exploring AI
  • Development with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Fine-Tuning LLMs, AI Agentic workflows, LangChain, LangGraphs, and Cascading models
  • Experience in deploying in hybrid, multi-cloud architecture and edge computing
  • Extensive experience architecting and shipping large-scale distributed software systems
  • Ability to identify gaps and bottlenecks, and develop solutions to optimize performance
  • Strong programming and software development skills in JAVA, Python, Shell-script along with good understanding of distributed systems and REST APIs
  • Experience in working with SQL/NoSQL database systems such as MySQL, Cassandra, MongoDB or Elasticsearch
  • Excellent knowledge and working experience with Docker containers and Virtual Machines
  • Good background of Cloud technologies like OpenStack, Docker, Kubernetes, Chef/Puppet, Hadoop/Ceph/SwiftStack, LXC, Git, Perforce, JFrog, Kafka
  • Ability to work across organizational boundaries optimally to improve alignment and productivity between teams in a multi-national, multi-time-zone corporate environment
Responsibilities
  • Serve as an Architect developing internal AI systems used by thousands of NVIDIAns globally
  • Identify gaps and issues and resolve ones are better suited for AI solutions versus conventional approaches
  • Further divide the AI category into 'buy versus build' options by researching available tools in the market
  • Align with teams across Nvidia to establish overall AI system goals and break them down into specific objectives for each sub-system
  • Drive, motivate, convince, and mentor sub-system leads to achieve improvements with agility and speed
  • Identify performance bottlenecks and optimize the speed and cost efficiency of AI development and testing systems
  • Drive the planning of software/hardware capacity, covering both internal and public cloud, addressing the balance between time and utilization
  • Introduce technologies enabling massively parallel systems to improve turnaround time by an order of magnitude
  • Collaborate with AI product vendors to gain deep insights of the AI industry, and share them with leaders and developers internally
Desired Qualifications
  • MS or PhD in EE/CS
  • Depth in AI, Machine Learning and Deep Learning algorithms and techniques
  • Strong collaborative and interpersonal skills, with a consistent record of guiding and influencing others in dynamic environments
  • Experience developing large-scale software systems using service-oriented architecture under real-time performance requirements
  • Background in designing high-performance, scalable software systems with a strong focus on hardware cost optimization

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

Simplify Jobs

Simplify's Take

What believers are saying

  • Agentic AI adoption at scale drives major inflection in inference demand globally.
  • Jensen Huang projects $3T-$4T global AI factory buildout through 2030.
  • Data centre networking revenue surged 263% YoY to $10.98B in Q4 FY2026.

What critics are saying

  • Nemotron 3 open weights enable AMD and Intel to replicate NVIDIA's software moat.
  • Insider selling over three months signals executive doubt about sustaining 73% growth.
  • $30B OpenAI investment exposes NVIDIA to catastrophic losses from governance collapse.

What makes NVIDIA unique

  • Vera Rubin launching July 2026 reduces inference token costs tenfold versus Blackwell.
  • Nemotron 3 Nano Omni achieves 9x higher throughput on consumer hardware like RTX 4090.
  • Clear datacenter product roadmap extends through 2028 with Feynman arriving in 2028.

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Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

-1%

1 year growth

-3%

2 year growth

-2%
The Associated Press
Apr 15th, 2026
Matlantis integrates NVIDIA ALCHEMI Toolkit for 10x faster materials simulation

Matlantis has integrated NVIDIA's ALCHEMI Toolkit into its materials simulation platform to accelerate industrial materials discovery. The company previously incorporated NVIDIA Warp-optimised kernels, achieving up to 10x speed improvements in atomistic calculations. The integration includes LightPFP, Matlantis' lightweight potential for large-scale simulations, which uses a server-based architecture with NVIDIA ALCHEMI Toolkit-Ops to reduce communication bottlenecks. Matlantis plans to integrate its flagship Universal Machine-Learning Interatomic Potential with the toolkit to further enhance GPU efficiency. Launched in 2021, Matlantis is a cloud-based atomistic simulator jointly developed by PFN and ENEOS. The platform uses deep learning to increase simulation speeds by tens of thousands of times and serves over 150 companies discovering materials including catalysts, batteries and semiconductors.

CNBC
Apr 14th, 2026
Nvidia stock surges 18% on 10-day winning streak fuelled by $1T GPU orders through 2027

Nvidia shares have climbed 18% over a ten-day winning streak, the longest since 2023. The stock is trading about 8% below its October all-time high of $212.19. CEO Jensen Huang revealed at last month's GTC conference that Nvidia has over $1 trillion in GPU orders through 2027, including Blackwell and next-generation Vera Rubin chips. Data centre revenue surged 75% year-over-year and now comprises 88% of the business, a dramatic shift from five years ago when gaming dominated. The rally follows major deals including Meta's February commitment to deploy millions of Nvidia chips across its global data centres. On Monday, Nvidia denied rumours it was pursuing acquisitions of PC makers Dell or HP. The company also unveiled Ising, a new family of open-source models for quantum computing.

Yahoo Finance
Apr 14th, 2026
D-Wave CEO claims quantum computers could challenge Nvidia's AI dominance with superior power efficiency

D-Wave Quantum CEO Alan Baratz claims quantum computing poses a threat to Nvidia, citing superior energy efficiency. Speaking at the Semafor World Economy Summit, Baratz said D-Wave's quantum computer uses just 10 kilowatts of power—equivalent to five or 10 GPUs—whilst solving problems that would take GPU systems nearly a million years. D-Wave shares rose nearly 16% on Tuesday, part of a 140% gain over the past year. The company reported $2.75 million in Q4 revenue, missing analyst estimates, but bookings surged 471% to $13.4 million. The $5.3 billion company recently secured a $20 million agreement with Florida Atlantic University and acquired Quantum Circuits for $550 million. However, quantum machines remain specialised tools, unable to run large language models that drive Nvidia's dominance.

Yahoo Finance
Apr 14th, 2026
Vertiv partners with Nvidia on AI data centre infrastructure as analysts raise price target to $300

Vertiv Holdings has been reaffirmed with a Buy rating by Evercore ISI, setting a price target of $280, whilst Barclays raised its target from $281 to $300 with an Overweight rating. The electrical equipment company is partnering with Nvidia on AI infrastructure development. On 16th March, Nvidia introduced its Vera Rubin DSX AI Factory reference design, with Vertiv providing critical power and cooling solutions for AI data centres. The partnership integrates Vertiv's infrastructure expertise with Nvidia's AI systems to enhance energy efficiency and performance. Vertiv is developing Vertiv OneCore Rubin DSX, a prefabricated system designed to accelerate AI factory deployment. The Brussels-headquartered company specialises in critical digital infrastructure technologies for data centres and communication networks.

Yahoo Finance
Apr 14th, 2026
Nvidia and Dell: AI infrastructure stocks to buy ahead of May earnings

Nvidia and Dell Technologies are positioned as attractive AI infrastructure investments ahead of their May earnings reports, according to recent analysis. Both companies supply critical hardware for AI computing, with demand for AI capacity continuing to outpace available resources across major cloud services. Nvidia shares have remained flat for six months despite strong fundamentals. Last quarter, its data centre business generated $62 billion in revenue, up 75% year over year, with a 75% gross margin. The company expects over $1 trillion in cumulative orders for its Blackwell and upcoming Rubin chips through 2027. Trading at 17 times next year's expected earnings, Nvidia's valuation appears discounted relative to its 66% revenue growth in fiscal year 2026. Dell Technologies similarly stands to benefit from the AI infrastructure build-out. Both companies report earnings in May.