Senior AI Engineer (Tools & Agents)

Join TwelveLabs as a Senior AI Engineer, where you'll be responsible for the integration layer that makes our video AI accessible to the world. You'll own the design and operation of our MCP server and agent-to-agent interfaces, as well as the authentication and access substrate. You'll also work closely with our research team to turn cutting-edge video and image understanding capabilities into durable product surfaces. This role requires versatility across the full platform surface and experience in building production systems, authentication and authorization, and enterprise readiness.

• Posséder l'intégration de la couche qui rend l'IA vidéo de TwelveLabs accessible au monde.
• Concevoir et construire l'interface d'intégration orientée vers les agents, le serveur MCP de TwelveLabs et les interfaces agent-à-agent.
• Travailler en étroite collaboration avec l'équipe de recherche pour transformer les capacités de compréhension vidéo et d'image en surfaces de produit durables.
• You bring versatility across the full platform surface. We're not looking for a specialist in one of these areas. We're looking for someone who can own all of them and make good tradeoffs across them
• You've shipped real agentic or LLM-powered systems. Not demos, but production systems with real users and real failure modes you had to debug and fix. You can talk about what broke, why, and what you changed
• You've built authentication and authorization in production, OAuth, OIDC, RBAC, or multi-tenant isolation, as a primary owner and not a consumer of someone else's framework
• You've thought seriously about enterprise-readiness: what it takes to go from a capability that works to a platform that a large customer will trust with their data and workflows
• You've operated in a fast-moving environment before, a startup, a hypergrowth company, or an AI-first team where you shipped under ambiguity without heavy process support
• You understand how retrieval, reasoning, and agent orchestration fit together as a system. Jockey's architecture sits at that intersection, and the integration surfaces you build need to reflect how that system actually behaves under real conditions
• You've owned a developer-facing or external API end-to-end, with real decisions about contracts, versioning, and the experience of building on top of your surface
• Hypergrowth pedigree from a technically excellent startup
• Experience with MCP, A2A protocols, or the broader agent ecosystem. You've contributed to or built on these surfaces and understand where they're headed