Senior/Staff Software Engineer, Forward Deployed

fal

San Francisco, CA

On-site

Who this role is best for

Candidates with enterprise technical integration experience and a background in AI/ML will find this customer-facing, highly technical role in San Francisco.

Best fit for

Candidates with experience in serverless and AI/ML production environments and a history of customer onboarding
— “Experience working with customers in a technical capacity”
Individuals who have translated customer feedback into product requirements and engineering tasks
— “Translate customer feedback into clear product specs, tasks, and engineering priorities”
Engineers who have built custom integrations or proofs-of-concept to solve customer deployment issues
— “Build custom proofs-of-concept or lightweight integrations to unblock adoption”

Things to consider

This role requires a high level of technical ownership and direct customer interaction.
— “You’ll join customer calls, deeply understand their architecture and needs”
The position demands comfort with ambiguity and fast-moving, low-process environments.
— “Comfort operating in a fast-moving, low-process environment”

How to stand out

Highlight experience with end-to-end debugging across frontend, backend, and infra layers.
— “Debug customer issues end-to-end across frontend, backend, and infra layers”
Showcase ability to identify and implement repeatable patterns from customer needs.
— “Identify repeatable patterns across customers and turn them into reusable product features”
Emphasize background in observability tools and cloud-native deployment practices.
— “Familiarity with observability tooling (logs, metrics, tracing)”
Demonstrate a track record of creating documentation or onboarding guides for technical audiences.
— “Experience writing documentation, onboarding guides, or customer playbooks”
Position yourself as someone who can bridge technical and non-technical stakeholders effectively.
— “Ability to understand complex systems and communicate clearly with both technical and non-technical stakeholders”

Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

successful deployment and scaling of AI workloads
customer feedback translated into actionable product specs
improved internal tooling based on customer pain points

Typical background

5+ years of engineering backgroundexperience working with customers in a technical capacity

Skills & requirements

Required

TypeScriptPythonPostgreSQLNext.jsServerless PlatformsObservability ToolingDistributed SystemsKubernetesCloud-native DeploymentAi/ml Workloads In ProductionGenerative AI InferenceWriting DocumentationOnboarding GuidesCustomer Playbooks

Preferred

Ai-native ProductsHigh-performance InferenceOrchestrationObservabilityEnterprise NeedsCustom Proofs-of-conceptLightweight IntegrationsReusable Product FeaturesInternal ToolingOnboarding FlowsDocs

Stack & domain

TypeScriptPythonPostgreSQLNext.jsCommunicationProblem-solvingTeamworkAIServerlessCloud

About the role

Original posting from fal via Ashby

fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products.
As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on.
ABOUT THIS ROLE:
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.
What you’ll do:
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
Qualifications/Nice-to-haves:
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: you take responsibility for customer success end-to-end
Comfort operating in a fast-moving, low-process environment
Experience with serverless platforms, infra 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
What we offer at fal:
Interesting and challenging work
A lot of learning and growth opportunities
Health, dental, and vision insurance (US)
Regular team events and offsites
U.S. EQUAL EMPLOYMENT OPPORTUNITY INFORMATION:
fal provides equal employment opportunities to applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other classification protected by applicable law.

Source: fal careers (Ashby)