Architect and build high-performance, distributed infrastructure to support agentic AI workflows, leveraging C++ to ensure low-latency agentic systems for real-world enterprise loads.

Take full ownership of the technology stack, transitioning experimental models into production services while ensuring system reliability, observability, and fault tolerance in multi-agent environments.

Drive inference cost optimization and system efficiency by implementing efficient connectors, optimize kernels, manage memory usage, and reduce latency to ensure AI solutions are not just powerful, but economically viable and at scale.

Provide technical guidance on system architecture and code quality, fostering a culture of engineering excellence through design reviews, code audits, and the adoption of best practices.

Maintain a tight loop between hypothesis and deployment by quickly prototyping new capabilities and seamlessly harden them for production release while focusing customer needs.

Bachelor’s degree or equivalent practical experience.

8 years of experience in software development focusing on infrastructure engineering in C++.

5 years of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), or specialization in another ML field.

5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.