Senior Software Engineer, Full Stack (Serverless)

🏢 Fal Ai · 📍 San Francisco · ⏰ FullTime

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Position Summary & Responsibilities

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 Full Stack Engineer on Serverless, you will build the core product across frontend and backend that powers fal’s Serverless platform. This is a deeply product-focused role. You will work side-by-side with Product and Infrastructure to design and ship reusable, scalable systems that enterprise customers rely on in production every day.

You will be a foundational technical owner of fal Serverless as it scales to thousands of enterprise customers, with real responsibility, autonomy, and impact. This is a chance to help build a new product vertical from the ground up inside a company that is already scaling at rocket-ship speed.

What you’ll work on:

Build and maintain core Serverless UI features (dashboards, logs, observability, configuration, usage)
Design and implement backend APIs that power the Serverless product experience
Improve performance, reliability, and scalability of customer-facing systems
Work closely with Infrastructure to ensure product features align with platform capabilities
Own features end-to-end, from design through production and iteration

Qualifications:

Minimum 5+ years experience working across both frontend and backend
Ability to conte

🎯 Candidate Preparation Guide For Fal Ai Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Evaluators obsess over extreme systems performance, ultra-low latency inference, and distributed GPU infrastructure optimization.

📋 Preparation Priorities (Key Areas to Clarify):

1. Treating GPU infrastructure as a black box managed entirely by cloud provider defaults.
2. Showing weakness in systems-level programming, memory management, or networking.
3. Focusing exclusively on model training while ignoring the realities of high-throughput inference.

✨ Recommended Role Alignment Hook:

I engineer high-throughput, ultra-low latency GPU inference pipelines that push generative models to their performance limits.

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