Forward Deployed Engineer

fal•San Francisco, CA

4h•$150,000 - $230,000•Onsite

About The Position

fal is building the fastest and most scalable infrastructure for AI inference. Fal Serverless powers 1,300+ endpoints on the fal Marketplace and handles tens of millions of requests per day across production workloads. Enterprises use fal Serverless to deploy, operate, and scale custom AI models without managing infrastructure themselves. Autoscaling, observability, and operational complexity are handled end-to-end by fal’s platform and UI. Serverless began as internal infrastructure built to support fal’s own scale and was released publicly to enterprise customers in early 2025. It is now a core, revenue-driving product with rapidly growing adoption. fal is one of the fastest-growing AI startups, reaching Series D at a $4.5B valuation with a lean team of ~70 employees. You’ll be joining early, with meaningful ownership and direct impact on a foundational product. 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. This is a highly technical, customer-facing role where you’ll act as the bridge between Sales, Product and Infrastructure teams. You’ll join customer calls, deeply understand their architecture and needs, and translate those into actionable implementation plans and product requirements. You will be responsible for unblocking customer deployments, accelerating onboarding, and ensuring enterprise accounts successfully reach production fast. This is a role for someone who loves solving real-world engineering problems and wants direct ownership over outcomes that drive revenue and product growth.

Requirements

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 Haves

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

Responsibilities

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