Senior AI Engineer, Tools & Agents

TwelveLabs · Posted today

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Eligibility

United States

Type

Full-time

Posted

today

Who we are

At Twelve Labs, we are pioneering the development of cutting-edge multimodal foundation models that have the ability to comprehend videos just like humans do. Our models have redefined the standards in video-language modeling, empowering us with more intuitive and far-reaching capabilities, and fundamentally transforming the way we interact with and analyze various forms of media.

With a remarkable $107 million in Seed and Series A funding, our company is backed by top-tier venture capital firms such as NVIDIA’s NVentures, NEA, Radical Ventures, and Index Ventures, and prominent AI visionaries and founders such as Fei-Fei Li, Silvio Savarese, Alexandr Wang and more. Headquartered in San Francisco, with an influential APAC presence in Seoul, our global footprint underscores our commitment to driving worldwide innovation.

We are a global company that values the uniqueness of each person’s journey. It is the differences in our cultural, educational, and life experiences that allow us to constantly challenge the status quo. We are looking for individuals who are motivated by our mission and eager to make an impact as we push the bounds of technology to transform the world. Join us as we revolutionize video understanding and multimodal AI.

About the Role

TwelveLabs builds multimodal AI that understands video the way people do. We're looking for a product-minded senior backend engineer to build and own the platform and integration surfaces that bring our video-understanding capabilities to developers and AI agents.

You'll shape the APIs, the agent-facing interfaces, and the authentication, authorization, and multi-tenancy that make them production-grade and enterprise-ready. This is high-ownership, high-craftsmanship work at the frontier of agentic AI, with a direct line from what you build to what our customers and partners can do.

This role is hybrid, based in our San Francisco office.

Candidates must be able to travel up to 10% of the time annually to attend conferences, off-site meetings, and other business-related events as required by the role. This role may require participation in on-site interviews and/or completion of in-person onboarding processes.

In this role, you will

Design and own developer- and agent-facing surfaces: public and partner APIs, and agent integration interfaces such as MCP and agent-to-agent protocols.
Build the authentication and authorization substrate: how users and machines authenticate, and how access is enforced (RBAC, organization and team scoping).
Ship enterprise-readiness capabilities: organization support, per-API-key usage tracking and metering, and rate limiting designed around real system constraints rather than arbitrary defaults.
Keep the platform reliable and scalable: define and uphold SLOs, harden failure paths, and keep services healthy under real-world and multi-tenant load.
Move fast without compromising quality, shipping to customers on a tight loop while holding a high craftsmanship bar.
Collaborate closely with engineering and research partners to turn cutting-edge capabilities into durable product surfaces.

You may be a good fit if you have

Strong backend engineering depth (typically 6+ years) building and operating production services and APIs at scale.
A track record of owning developer-facing or platform surfaces such as public APIs, SDKs, or integration layers, with real care for API design and contracts.
Hands-on experience with authentication and authorization in production: OAuth/OIDC, RBAC, multi-tenant isolation.
Experience building enterprise/SaaS platform concerns: organization and team models, usage metering, rate limiting, quotas.
Demonstrable, hands-on experience with agentic systems, in production or through substantial personal projects, with a strong grasp of agent tool design, MCP and function-calling, and the failure modes of LLM-driven applications.
The judgment to ship fast and the craftsmanship to do it well, with the maturity to know which one a given problem calls for.

Preferred Qualifications

Shipped an agent or LLM-powered product that real users or developers depend on, and can speak to what broke at scale and how you fixed it.
Have taken a product from early access to enterprise-grade: the auth, multi-tenancy, and reliability work that turns a capability into something a large customer will trust.
Contributed to the agent tooling ecosystem (for example, open-source MCP servers or agent frameworks) or have a body of personal work that shows real fluency.