Software Engineering Team Lead

For many of us there's that one podcast we never miss, and video content is part of our daily routine, whether it's professional or personal. But how many of us truly understand the effort that goes on behind the scenes? Here at Riverside, we know it well. That's exactly why we built an AI-powered platform that helps content creators, podcasters, marketers, and more at major brands like Netflix, Disney, Google, and Microsoft to create high-quality content with ease.

Riverside's technology streamlines the entire content creation process, turning ideas into professional-grade content with the highest production standards, without requiring expensive equipment or external services. The secret? AI-driven tools that replace traditional production roles like editing, directing, and design, automating the entire process at the click of a button.

About the Co-Creator Team

The Co-Creator team is at the heart of Riverside's AI vision. We're not just integrating AI into a product; we're building an autonomous creative agent that works alongside users to ideate, edit, and produce content end-to-end. Think of it as a virtual co-creator: an AI partner that understands context, remembers preferences, uses tools, reasons through creative decisions, and takes action on behalf of the user.

This is not a wrapper around an LLM. The Co-Creator is a full agent system with working memory, dynamic personas, tool-calling capabilities, and a purpose-built Agent-to-UI (A2UI) layer that streams reasoning and actions to the user in real time. You'll be leading the team that designs, builds, and ships this system.

What You'll Do

• Lead a team of engineers building Riverside's core AI agent, from prompt architecture and tool orchestration to the real-time UI that makes the agent's thinking visible and actionable.
• Own the full agent stack: working memory, dynamic persona infrastructure, context management, tool calling, and integration with backend AI services.
• Drive architectural decisions around agent reliability, latency, and user trust, including how the agent reasons, when it asks for confirmation, and how users review and act on its suggestions.
• Build and iterate on MCP integrations that extend what the agent can do, connecting it to publishing platforms, media tools, and external services.
• Collaborate with Product and Design to shape the agent experience: making AI reasoning transparent, interactions natural, and outputs high-quality.
• Champion engineering quality through observability (Langfuse), E2E testing, and CI/CD automation on prompts and agent behavior.
• Grow your team members technically, help them navigate ambiguity (agent development is full of it), and maintain high velocity on a fast-moving roadmap.