# Senior Solutions Architect, Generative AI Deployment and AIOps

**Company**: NVIDIA
**Location**: Santa Clara, CA
**Work arrangement**: remote
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Solutions-Architect--Generative-AI-Deployment-and-AIOps_JR2024468?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_470d76f8-602

## Description

NVIDIA is seeking outstanding AI Solutions Architects to assist and support customers that are building solutions with our newest AI technology.

As a Senior Solutions Architect, Generative AI Deployment and AIOps, you will become a trusted technical advisor with our customers and work on exciting projects and proof-of-concepts focused on inference for Generative AI and Large Language Models (LLMs).

**Responsibilities:**

- Partner with solution architects, engineering, product, and business teams to understand their strategies and technical needs and help define high-value solutions

- Engage with developers, scientific researchers, and data scientists to gain experience across a range of technical areas

- Collaborate with lighthouse customers and industry-specific solution partners targeting our computing platform

- Work closely with customers to help them adopt and build creative solutions using NVIDIA technology and MLOps solutions

- Analyze performance and power efficiency of AI inference workloads on Kubernetes

- Travel to conferences and customers may be required (20%)

**Requirements:**

- BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (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, especially in Python

- Proficiency in problem-solving and debugging skills in GPU orchestration and Multi-Instance GPU (MIG) management within Kubernetes environments

- Experience with containerization and orchestration technologies, monitoring, and observability solutions for AI deployments

- Excellent knowledge of the theory and practice of LLM and DL inference

- Excellent presentation, communication, and collaboration skills

**Preferred Qualifications:**

- Prior experience with DL training at scale, deploying or optimizing DL inference in production

- Experience with NVIDIA GPUs and software libraries such as NVIDIA NIM, Dynamo, TensorRT, TensorRT-LLM

- Excellent C/C++ programming skills, including debugging, profiling, code optimization, performance analysis, and test design

- Familiarity with parallel programming and distributed computing platforms

## Skills

### Required
- Deep Learning
- Python
- Kubernetes
- GPU orchestration
- Multi-Instance GPU (MIG) management
- Containerization
- Orchestration technologies
- Monitoring
- Observability solutions
- LLM inference
- DL inference

### Nice to have
- DL training at scale
- Deploying DL inference in production
- Optimizing DL inference
- NVIDIA GPUs
- NVIDIA NIM
- Dynamo
- TensorRT
- TensorRT-LLM
- C/C++ programming
- Parallel programming
- Distributed computing platforms

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Solutions-Architect--Generative-AI-Deployment-and-AIOps_JR2024468?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)