Build and operate end-to-end backend systems for AI creative tools, spanning application data layers, ML inference services, APIs, and Kubernetes infrastructure. The role requires production ownership, architectural judgment, and comfort working across the stack; typically 4–8 years of experience is preferred.
Salary not listed
On-site4+ YOEBackend Engineering
About the role
Responsibilities
Build and operate backend systems across the SvelteKit application and its Postgres, Redis, and ClickHouse data layers.
Develop Python services that run machine-learning inference.
Operate Kubernetes clusters across multiple cloud and GPU providers.
Own systems end-to-end, from design through production operations.
Build durable execution for long-running workflows, including state machines, idempotency, and retry semantics for multi-step inference jobs.
Improve the public API with a clean, well-documented API surface and OpenAPI documentation generated from Zod schemas.
Build enterprise features such as access-control lists, audit logs, and entitlements.
Requirements
Experience owning real production systems end-to-end, including design, monitoring, metrics, and incident response.
Typically 4–8 years of experience, with scope and engineering judgment valued over resume tenure.
Comfortable working across the stack and adapting to unfamiliar codebases.
Able to make architectural decisions for scalable systems.
Clear written and verbal communication.
Comfortable working independently without extensive product-management direction.
Nice-to-haves
GPU or infrastructure experience.
Experience running Kubernetes in production.
A creative background.
Technology
SvelteKit
TypeScript
Python
Postgres and AWS Aurora
Redis
ClickHouse
Docker
Kubernetes
FluxCD
Compensation and Benefits
Competitive compensation with salary and equity packages.
100% of employee health insurance premiums and 99% of dental and vision premiums covered.
Health FSA accounts and long-term disability coverage.
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