Senior Solutions Architect, Agentic AI

What You’ll Be Doing

• Deliver innovative and optimized AI agents using the latest techniques including Test Time Compute, Reinforcement Learning, inference optimization and model fine-tuning.
• Engineer new solutions to fit customers needs by integrating their enterprise data sources into meaningful agentic applications.
• Work with agentic frameworks to develop applications that retrieve and generate insights from enterprise data, including text, code, and images.
• Create high-impact solutions such as deep research assistants, multi-modal dialogue systems, and task-specific agents that support a wide range of enterprise workflows.
• Engage deeply with engineering teams, stay ahead of the latest AI advancements, and apply strong technical judgment to everything you deliver.
• Provide direct feedback from first-time implementations to improve software products and scale knowledge by educating vertical teams and building communities on NVIDIA AI software products.

What We Need To See

• BS, MS, or Ph.D. degree in Engineering, Mathematics, Physics, Computer Science, Data Science, or similar (or equivalent experience).
• 12+ years experience demonstrating an established track record in Deep Learning and Machine Learning.
• Strong software engineering and debugging skills, including experience with Python, C/C++, and Linux.
• Experience with GPUs as well as expertise in using deep learning frameworks such as TensorFlow or PyTorch.
• Proficiency in rapid prototyping using Python with strong foundational knowledge of data structures, algorithms, and software engineering principles.
• Experience with building advanced multi-agent systems, using libraries like LangGraph, LlamaIndex, CrewAI.
• Ability to multitask effectively in a dynamic environment, as well as clear written and oral communications skills with the ability to effectively collaborate with executives and engineering teams.

Ways To Stand Out From The Crowd

• Expertise in building evaluation harnesses, success metrics, automated testing pipelines, and guardrail frameworks to ensure agentic AI workflows are safe, reliable, and production-ready.
• Skilled in fine-tuning and optimizing reasoning-focused LLMs and SLMs, including prompt engineering, quantization, and benchmarking.
• Experience developing production-grade deployment patterns using Kubernetes/OpenShift, CI/CD automation, and secure cloud-native infrastructure.

Pay

Base salary range: 224,000 USD - 356,500 USD. You will also be eligible for equity and benefits.