AI Engineer

Staff AI Engineer

At Podium, our mission is to arm every local business with a complete platform and outcome-driven AI employees that convert leads into real, paying customers. Every day, millions of workers use our AI lead conversion and communication platform to help them get more leads and make more money.

Our work and focus on helping local businesses thrive has been recognized across the industry, including Forbes’ Next Billion Dollar Startups, Forbes’ Cloud 100, the Inc. 5000, and Fast Company’s World’s Most Innovative Companies.

At Podium, we believe in fostering a culture that thrives on hiring and developing exceptional talent. Our operating principles serve as a compass, guiding daily behavior and decision‑making, and ensure we hire people who will thrive  you resonate with our operating principles and are energized by our mission, Podium will be a great place for you!

We are looking for a talented Staff AI Engineer to help build and scale our AI Agent platform—a powerful system that autonomously interacts with customers, handling millions of conversations every month. In this role, you’ll design and deliver the software that enables local businesses to manage complex customer interactions automatically, book more appointments, and serve their customers more effectively across multiple channels (e.g., voice, SMS, chat).

If you thrive in fast‑paced, highly iterative environments, enjoy solving complex distributed systems challenges, and want to see your work drive immediate business impact, this role is for you!

• Build and scale the AI Agent platform — enabling high‑volume, real‑time conversational workflows that deliver accuracy and low latency at scale.
• Design and implement APIs, services, and infrastructure that power multi‑turn, cross‑channel customer interactions.
• Own the full lifecycle: architecture, implementation, deployment, and ongoing reliability.
• Prototype rapidly, iterate with live interaction data, and continuously improve system performance and user experience.
• Implement observability, monitoring, and operational best practices to ensure reliability in production, focusing on agent accuracy and latency.
• Collaborate with engineers, product managers, and AI/ML scientists to deliver end