Solutions Architect

📋 Description

• Design intricate agentic systems that incorporate multi-agent coordination, long-horizon reasoning, and sophisticated planning frameworks.

• Create comprehensive solutions, including domain-specific enterprise agents and high-performance retrieval pipelines (RAG) that utilize various data sources.

• Enhance inference performance by leveraging GPU-accelerated frameworks and the complete NVIDIA AI infrastructure stack.

• Develop practical Proofs of Concept (PoCs) and reference architectures that act as a foundation for production-quality generative AI pipelines.

• Work collaboratively with Enterprise ISVs to embed NVIDIA software into native platforms, expediting the rollout of production workloads.

• Partner with various internal teams to refine NVIDIA software based on insights gathered from real-world applications.

• Support partner engineering teams through technical workshops, in-depth architecture assessments, and developer enablement initiatives.

• Expand global expertise by creating reusable resources and documentation to assist field teams in deploying agentic AI at scale.

⛳️ Requirements

• BS/MS/PhD in Computer Science, Electrical Engineering, AI/ML, or a related field.

• Over 5 years of experience in deep learning, machine learning, or distributed AI systems.

• Proficient in programming and debugging within Python, C/C++, and Linux environments.

• Familiarity with deep learning libraries such as PyTorch or TensorFlow.

• Practical experience in developing LLM and generative AI applications.

• Experience with agentic or multi-agent AI systems utilizing frameworks like: 1. LangGraph 2. LlamaIndex 3. CrewAI 4. LangChain 5. OpenAI Agents SDK or comparable orchestration frameworks.

• Experience in building tool-using AI agents that engage with APIs, databases, and enterprise systems.

• Capability to swiftly prototype AI applications and construct scalable GPU-accelerated architectures.

• Strong interpersonal skills and the ability to collaborate effectively with engineering teams, partners, and executive stakeholders.

🏝️ Benefits

• Equity

• Benefits