FAL

FAL

Senior Software Engineer, Backend

San Francisco · Senior

Sponsorship not specified$180k-$250kDetected 62 days ago
PythonGoDistributed SystemsBackend DevelopmentCode ReviewGitKubernetesCI/CDKafkaAirflow

About the role

  • This role is ideal for engineers who thrive on complex distributed systems and have deep experience with backend APIs, relational databases, and event-driven architectures.
  • You'll build high-performance, reliable solutions across cloud-native platforms and global infrastructure for a fast-scaling, commerce-driven company.

Responsibilities

  • Identify, design, and develop foundational backend services that power Fal's commerce platform
  • Partner with product teams to understand functional requirements and deliver solutions that meet business needs
  • Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance
  • 5+ years of demonstrated experience in building large scale, fault tolerant, distributed systems and API microservices

Requirements

  • Experience designing, analyzing and improving efficiency, scalability, and stability of various system resources
  • Proficiency in writing and maintaining Infrastructure as Code (IaC)
  • Proficiency in version control practices and integrating IaC with CI/CD pipelines.

Nice to have

  • Experience with payment processors (e.g. Stripe) and billing systems a plus
  • Experience with Kubernetes, or containers a plus

Skills

  • fal is the generative media ecosystem powering the next generation of AI products.

Compensation

  • $180,000 - $250,000 + equity + comprehensive benefits package
  • We are currently hiring in downtown San Francisco.

Benefits

  • Competitive salary and equity
  • A lot of learning and growth opportunities
  • Health, dental, and vision insurance (US)

Company info

  • We are currently hiring in downtown San Francisco.
  • We offer relocation assistance to San Francisco.

This listing is sourced directly from FAL's careers page and normalized into a canonical job model.