Job Description
- Job Description:
- Serve as a trusted technical advisor to the next generation of AI-native companies building category-defining applications such as developer copilots, AI search engines, agentic platforms, and multimodal creative tools.
- Work directly with startup founders and engineering teams to architect and optimize AI workloads using NVIDIA technologies including CUDA-X libraries, TensorRT-LLM, Triton Inference Server, NVIDIA NeMo, NIM microservices, and GPU-accelerated data processing frameworks.
- Help AI-native companies scale training and inference infrastructure, optimizing model performance, cost efficiency, and latency across NVIDIA accelerated computing platforms.
- Guide startups through complex architectural decisions including model optimization, inference scaling, agent frameworks, multimodal pipelines, and real-time AI systems.
- Collaborate closely with NVIDIA engineering, research, product, and go-to-market teams to identify emerging AI-native categories and influence NVIDIA’s platform roadmap.
- Build strong relationships with founders, CTOs, and technical leaders across the AI-native ecosystem to ensure NVIDIA is the platform of choice for the most innovative AI companies.
- Support the creation of reference architectures, AI blueprints, and best practices that enable AI-native companies to deploy scalable AI applications and agentic systems.
- Partner with NVIDIA’s Industry Business Development teams, Solutions Architects, and Account Managers to accelerate adoption of NVIDIA technologies across high-growth AI-native companies.
- Requirements:
- BS/MS degree or equivalent experience in Computer Science, Engineering, or a related field
- 5+ years of experience in software engineering, developer relations, solutions architecture, technical partnerships, or product management within AI, developer platforms, or large-scale software systems
- Hands-on experience building or scaling AI-powered products, developer platforms, or large-scale cloud services
- Strong expertise in machine learning infrastructure, model serving, distributed systems, and real-time AI applications
- Deep understanding of the modern AI stack including LLMs, agent frameworks, multimodal models, and inference optimization
- Proven ability to work closely with engineering teams and startup founders to influence product architecture and technical roadmaps
- Exceptional communication skills and the ability to explain complex AI systems to audiences ranging from engineers to startup founders and executives
- Experience working within fast-moving startup environments or supporting high-growth developer ecosystems
- Benefits:
- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
- Equity
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