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NVIDIA

Senior Software Architect, Agentic AI

Posted Yesterday
Be an Early Applicant
In-Office
3 Locations
184K-357K
Senior level
In-Office
3 Locations
184K-357K
Senior level
The role involves implementing AI applications, collaborating with hardware architects, optimizing algorithms, and researching emerging AI technologies to improve engineering workflows.
The summary above was generated by AI

Are you passionate about generative AI and building agentic workflows to solve real problems? Are you interested in learning more about computer hardware architecture? NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our chips and systems power applications within artificial intelligence, computer graphics, autonomous vehicles, robotics, gaming, virtual reality, and high-performance computing.

We are now looking for a senior SW AI architect to help redefine our engineering flows. Come join the NVIDIA hardware architecture team to build agentic systems to improve our future chip designs, or put differently, use AI to design our next-generation AI systems!

What you’ll be doing:

  • Serve as an expert in implementing and deploying AI applications based on large language models (LLMs), internal and external agentic frameworks, and custom models.

  • Work with hardware architects to identify how to best design, customize, and deploy AI-based solutions to their specific problem domains.

  • Collaborate with infrastructure engineers to improve existing automated workflows by incorporating LLMs and establishing best practices for future solutions.

  • Develop and optimize retrieval and generation algorithms for enterprise data (text, code, and images) to build advanced AI applications.

  • Interact with internal research groups on how to solve complex chip design problems in new ways by leveraging machine learning (ML) and deep learning (DL).

  • Research emerging AI technologies and engineering best practices to continuously evolve our development ecosystem and maintain a competitive edge.

What we need to see:

  • MSc or PhD in Data Science, Computer Science/Engineering, Electrical Engineering, or equivalent experience.

  • 5+ years of industry or research experience.

  • Deep practical knowledge of LLMs, DL/ML, and Agent development.

  • Well versed in agentic literature and eager to continue learning.

  • Strong background in implementing AI solutions to solve real-world engineering problems.

  • Experience with training/fine-tuning custom models, building multi-agent systems, retrieval augmented generation (RAG) pipelines, and vector databases.

  • Strong analytical, communication, and interpersonal skills.

Ways to stand out from the crowd:

  • Background in computer architecture or hardware development.

  • Good understanding of distributed systems and microservice architecture.

  • Hands-on experience with NVIDIA Inference Microservices (NIMs).

NVIDIA engineers the most advanced chips, systems, and software for the AI factories of the future and is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and ambitious people in the world working for us. Are you a creative and autonomous engineer who wants to make a difference? If so, we want to hear from you! 

#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 22, 2025.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Top Skills

Artificial Intelligence
Deep Learning
Large Language Models
Machine Learning
Vector Databases

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