Solutions Architect, Agentic AI

• Strong foundational expertise, from a BS, MS, or Ph.D. degree in Engineering, Mathematics, Physics, Computer Science, Data Science, or similar (or equivalent experience).

• 5+ 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.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.