fal

Senior Software Engineer, Full Stack (Serverless)

fal
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9 hours ago

Base Salary

$180k - $230k/yr

Responsibilities

  • Build and maintain core Serverless UI features such as dashboards, logs, observability, configuration, and usage.
  • Design and implement backend APIs that power the Serverless product experience.
  • Improve the performance, reliability, and scalability of customer-facing systems.
  • Partner with Infrastructure to align product features with platform capabilities.
  • Own features end-to-end from design through production release and iteration.

Requirements

  • At least 5 years of experience working across both frontend and backend systems.
  • Proficiency with TypeScript, Python, Postgres, and Next.js.
  • Experience owning features end-to-end in production systems.
  • Ability to context-switch between UI, backend, and performance work.
  • Experience building developer platforms or infrastructure-adjacent products.
  • Familiarity with observability tooling including logging, metrics, and tracing in production environments.
  • Experience with generative AI inference, training, and compute systems.
  • Background in distributed systems, container orchestration, or cloud-native architectures.
  • Experience with real-time systems, streaming logs, or high-throughput data pipelines.
  • Exposure to Kubernetes, Prometheus, Datadog, gRPC, or similar systems.
  • Product-minded approach with emphasis on clean abstractions, maintainability, ownership, and entrepreneurial execution.

Benefits

  • Health, dental, and vision insurance for U.S. employees.
  • Learning and growth opportunities.
  • Regular team events and offsites.
  • Interesting and challenging work in a fast-moving, low-process environment.

Tech Stack

DatadoggRPCKubernetesNext.jsPostgreSQLPrometheusPythonTypeScript

Categories

fal

About fal

51-200 employees

Fal builds a generative media platform that gives developers a unified API to run state-of-the-art image, video, and audio models. It provides serverless GPUs, high-performance inference, and dedicated compute clusters so teams can customize, deploy, and scale models in production. The company is privately held and headquartered in San Francisco, serving both startups and enterprises through a commercial API and managed infrastructure.

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