Senior Solutions Architect, Generative AI Data Processing

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +3 · Remote

Senior Solutions Architect role focused on assisting customers in deploying Generative AI solutions, particularly for data processing and agentic workflows, using NVIDIA's AI technology stack. The role involves technical advisory, system design, and implementation at scale, with a strong emphasis on Deep Learning, LLMs, and GPU technologies.

What you'd actually do

  1. Design and implement scalable systems to accelerate agentic workflows and efficiently handle datacenter-scale use cases
  2. Partnering with other solution architects, engineering, product and business teams. Understanding their strategies and technical needs and helping define high-value solutions
  3. Dynamically engaging with developers, scientific researchers, and data scientists, gaining experience across a range of technical areas
  4. Strategically partnering with lighthouse customers and industry-specific solution partners targeting our computing platform
  5. Working closely with customers to help them adopt and build creative solutions using NVIDIA technology

Skills

Required

  • Machine Learning
  • Deep Learning
  • Data Analytics
  • Python
  • Programming
  • Optimizations
  • Software Design
  • Problem-solving
  • Debugging
  • Containerization
  • Orchestration
  • Monitoring
  • Observability
  • Presentation skills
  • Communication skills
  • Collaboration skills

Nice to have

  • AI at scale on cloud environments
  • NVIDIA GPUs
  • NVIDIA NeMo Framework
  • NeMo Retriever
  • cuVS
  • RAPIDS
  • MLOps
  • Kubernetes
  • Docker
  • Helm charts
  • Jupyter notebooks
  • C/C++ programming
  • Profiling
  • Code optimization
  • Performance analysis
  • Test design
  • Parallel programming
  • Distributed computing platforms

What the JD emphasized

  • 8+ years of hands-on experience with Machine Learning, Deep Learning and Data Analytics
  • Strong fundamentals in programming, optimizations, and software design, especially in Python
  • Experience with containerization and orchestration technologies, monitoring, and observability solutions for AI deployments

Other signals

  • Deploying AI solutions in production
  • Accelerate agentic workflows
  • Datacenter-scale use cases
  • MLOps
  • NVIDIA GPUs and software libraries