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Staff Forward Deployed Engineer

Works directly with enterprise customers to deploy and scale AI workloads on fal Serverless platform, debugging issues across frontend/backend/infra, translating needs into product specs, and building POCs. Requires strong TypeScript/Python/Next.js skills and customer-facing technical experience.

150k – 230kSan Francisco, CASolutions ArchitectureOnsite

About the role

What you’ll work on

  • Join enterprise onboarding calls and act as the technical owner for deployments
  • Help customers integrate their models into fal Serverless (APIs, scaling, observability, deployment workflows)
  • Debug customer issues end-to-end across frontend, backend, and infra layers
  • Translate customer feedback into clear product specs, tasks, and engineering priorities
  • Work closely with Product + Infra to ensure enterprise needs are shipped into the platform
  • Build custom proofs-of-concept or lightweight integrations to unblock adoption
  • Identify repeatable patterns across customers and turn them into reusable product features
  • Improve internal tooling, onboarding flows, and docs based on real customer pain points

What we’re looking for

  • Strong engineering background (Proficiency with TypeScript, Python, Postgres, and Next.js)
  • Experience working with customers in a technical capacity (Solutions Engineer, Forward Deployed Engineer, DevRel Engineer, or similar)
  • Comfortable jumping into ambiguous customer problems and finding solutions fast
  • Ability to understand complex systems and communicate clearly with both technical and non-technical stakeholders
  • Strong written communication skills (turning customer conversations into actionable specs/tasks)
  • Experience working across APIs, infrastructure, and cloud environments
  • High ownership mentality: you take responsibility for customer success end-to-end
  • Comfort operating in a fast-moving, low-process environment

Nice to have

  • Experience with serverless platforms, infra products, or developer platforms
  • Familiarity with observability tooling (logs, metrics, tracing)
  • Background in distributed systems, Kubernetes, or cloud-native deployments
  • Experience with AI/ML workloads in production
  • Experience writing documentation, onboarding guides, or customer playbooks

Compensation

$150,000 - $230,000 + equity + comprehensive benefits package

Skills

TypeScriptPythonPostgresNext.jsKubernetesAPIsServerlessObservabilityDistributed SystemsCloud Infrastructure

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