Solutions Architect, Scalability of Agentic Pipelines

NVIDIA’s Worldwide Field Operations (WWFO) team is looking for an AI focused Solution Architect with expertise in neural network inference and development/operation of agentic pipelines. A candidate with understanding of large scale DNN inference as well as end to end design of agentic utilities using tools such as NVIDIA NeMo Agent Toolkit, LangChain, LLamaIndex, Haystack, etc. In our Solutions Architecture team, we work with the most exciting computing hardware and software, driving the latest breakthroughs in artificial intelligence! We need individuals who can enable customer adoption of NVIDIA technology and develop lasting relationships with our technology partners, making NVIDIA an integral part of end-user solutions. We are looking for someone always thinks about artificial intelligence, someone who can thrive in a fast paced, rapidly developing field, someone able to coordinate efforts between customers, corporate marketing, industry business development and engineering.

A successful candidate will be working with groundbreaking NLP, LLM models that are fundamentally changing the way people use technology. As a Solutions Architect, you will be the first line of technical expertise between NVIDIA and our customers. Your duties will vary from working on proof-of-concept demonstrations, to driving relationships with key executives and managers to promote adoption of Large Language Models and streamline their deployment to production. Dynamically engaging with developers, scientific researchers, data scientists, IT managers and senior leaders is a significant part of the Solutions Architect role and will give you experience with a range of partners and technologies.

What You’ll Be Doing:

• Work directly with key customers to understand their technology and provide the best solutions.

• Develop and demonstrate solutions based on NVIDIA’s and open-source NLP and LLM technology and integrate them into agentic pipelines.

• Perform in-depth analysis and optimisation to ensure the best performance on GPU based systems. This includes inference optimisation but also optimisation of end to end agentic pipelines.

• Partner with Engineering, Product and Sales teams to develop, plan best suitable solutions for customers. Enable development and growth of product features through customer feedback and proof-of-concept evaluations.

• Build industry expertise and become a contributor in integrating NVIDIA technology into Enterprise Computing architectures.

What We Need to See:

• Excellent verbal, written communication, and technical presentation skills in English

• MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields

• A consistent record of academic and/or industry experience in fields related to machine learning, deep learning and/or data science with preference towards DNN inference.

• 8+ years of of experience.

• Work experience and knowledge of modern LLM, VLM, diffusion architectures with emphasis on MoE.

• Understanding of key libraries used for DNN inference (e.g. TRT-LLM, Dynamo, RedHat Inference Server) as well as agentic pipeline development.

• Excited to work with multiple levels and teams across organisations (Engineering, Product, Sales and Marketing team)

• Driven with strong analytical and problem-solving skills. You are a self-starter with demeanour for growth, passion for continuous learning and sharing findings across the team.

• Strong time-management and organisation skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very sophisticated projects

Ways to Stand Out from The Crowd:

• Experience working with inference of very large MoE architectures for NLP, CV, ASR or other.

• Experience using DevOps technologies such as Docker, Kubernetes, Singularity, etc.

• Understanding of HPC systems: data center design, high speed interconnect InfiniBand, Cluster Storage and Scheduling related design and/or management experience.