SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
fal is building the generative media ecosystem powering the next generation of AI products. The company provides infrastructure, tools, and model access that enable teams to move from idea to production at scale. fal offers a unified platform combining high-performance inference, orchestration, and observability for developers and enterprises building AI-native products.
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 where you act as the bridge between Sales, Product, and Infrastructure teams.
Key responsibilities include:
- Joining enterprise onboarding calls and serving 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
This role is ideal for someone who loves solving real-world engineering problems and wants direct ownership over outcomes that drive revenue and product growth.
Qualifications:
- 5+ years of 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: taking 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
- Experience writing documentation, onboarding guides, or customer playbooks
