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fal is building the generative media ecosystem and infrastructure powering the next generation of AI products. The company provides a unified platform combining high-performance inference, orchestration, and observability to help developers and enterprises move from idea to production at scale.
As a Forward Deployed Engineer on Serverless, you will work directly with enterprise customers to help them deploy, scale, and operationalize their AI workloads on fal's platform. This is a highly technical, customer-facing role serving as the bridge between Sales, Product, and Infrastructure teams.
Key responsibilities include:
- Joining enterprise onboarding calls and acting as the technical owner for customer deployments
- Helping customers integrate their models into fal Serverless, including APIs, scaling, observability, and deployment workflows
- Debugging customer issues end-to-end across frontend, backend, and infrastructure layers
- Translating customer feedback into clear product specifications, tasks, and engineering priorities
- Working closely with Product and Infrastructure teams to ensure enterprise needs are shipped into the platform
- Building custom proofs-of-concept or lightweight integrations to unblock customer adoption
- Identifying repeatable patterns across customers and turning them into reusable product features
- Improving internal tooling, onboarding flows, and documentation based on real customer pain points
You will have direct ownership over outcomes that drive both revenue and product growth, solving real-world engineering problems in a fast-moving environment.
Qualifications:
- 5+ years of engineering background with proficiency in 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 quickly
- Ability to understand complex systems and communicate clearly with both technical and non-technical stakeholders
- Strong written communication skills, particularly translating customer conversations into actionable specifications and tasks
- Experience working across APIs, infrastructure, and cloud environments
- High ownership mentality with responsibility for customer success end-to-end
- Comfort operating in a fast-moving, low-process environment
Nice-to-haves:
- Experience with serverless platforms, infrastructure products, or developer platforms
- Familiarity with observability tooling (logs, metrics, tracing)
- Background in distributed systems, Kubernetes, or cloud-native deployment
- Experience with AI/ML workloads in production
- Experience in generative AI inference, training, and compute space (strongly preferred)
- Experience writing documentation, onboarding guides, or customer playbooks
