Backend Engineer (1-3 Years, 60L)

About the role

Cardboard is looking for a Backend Engineer to build and own the systems that power video exports, media processing, generation workflows, and usage billing.

This is a hands-on engineering role for someone who enjoys reasoning about distributed state, queues, workers, retries, large files, and compute-heavy workloads. You’ll build reliable asynchronous systems, make large video workflows faster and more resilient, and continuously improve the economics of running them at scale.

You’ll work closely with the co-founder and engineering lead as an individual contributor, with significant ownership over technical decisions and production systems.

What you'll own

• Async processing pipelines. Design and build long-running jobs that can handle failures, retries, and partial completion while reporting progress clearly to users.
• Video asset pipelines. Build efficient systems for moving and processing large media files, including compression, pre-processing, storage, and selective synchronization.
• Codec and export workflows. Improve how video enters, moves through, and leaves the product, making export and transcoding workflows faster and more reliable.
• Credits and usage billing. Build accurate usage accounting across generation and compute workflows, including retries and failure scenarios, while preventing duplicate billing.
• Compute cost optimization. Identify expensive transcoding, GPU, storage, and generation workloads and redesign systems to improve their unit economics.
• Reliability and recovery. Reason carefully about distributed state, idempotency, retries, worker failures, and recovery so jobs behave predictably in production.
• Production infrastructure. Own the Kubernetes and DevOps work required to operate these systems reliably at Cardboard's current scale.

What we're looking for

• Strong backend engineering experience building and operating production systems.
• Experience designing stateful asynchronous workflows involving queues, workers, retries, job orchestration, and failure recovery.
• Strong experience with TypeScript as a backend language and comfort working with Python.
• Experience owning systems in environments where product requirements change quickly without compromising reliability.
• Strong understanding of idempotency, distributed state, concurrency, and failure handling.
• Experience identifying expensive workloads and improving compute efficiency or infrastructure costs.
• Comfort operating in a zero-to-one startup environment, making decisions independently and shipping frequently with limited structure.
• Experience using AI coding agents/tools while maintaining strong judgment around architecture, correctness, and production behavior.

Bonus Points

• Experience with FFmpeg, video codecs, transcoding, or media processing pipelines.
• Experience running GPU or other compute-intensive workloads.
• Experience building systems that process or transfer large media assets.
• Hands-on experience with Kubernetes and production infrastructure.