Senior AI SaaS Platform Architect / Lead Backend Developer

Senior AI SaaS Platform Architect / Lead Backend Developer

Project details:-

We are building an enterprise-grade AI SaaS platform for Lyrics, Music, Voice, and AI Video generation.

* Multi-Tenant Architecture
* White-label Platform
* AI Gateway
* Control Plane
* AI Plane
* Organizations
* Credits & Wallet
* Developer Platform
* Provider Adapter Architecture
* Feature-Based Subscription Engine
* Credits & Wallet System /Billing
* SDK Platform
* Developer Platform
* Enterprise API Platform
* AI Job Queue
* GPU Workers
* SDK
* Storage
* Analytics
* Notifications
* Admin Portal
* User Dashboard
* Admin Dashboard
* API/Partner Portal
* Super Admin Panel

# What You Will Build

The platform includes:

* AI Gateway
* Lyrics Engine
* Music Engine
* Voice Engine
* Video Engine
* Provider Adapter Layer
* Credits Engine
* Wallet
* Subscription Engine
* Feature Entitlement Engine
* Organization Management
* White-label Platform
* Developer Platform
* REST APIs
* SDK APIs
* Background Job Processing

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Our project will contain approximately:

* 70–80% → Use of trusted Open Source Components.
* 20–30% → Your Custom Platform and Business Logic.
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Our goal is to build a scalable AI platform similar in architecture to modern AI infrastructure platforms, while integrating open-source and commercial AI providers through a provider-independent architecture.

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# Technology Stack

Backend

* Python
* FastAPI
* PostgreSQL
* Redis
* Celery

Frontend

* Next.js
* MakerKit Lite
* Tailwind CSS

Infrastructure

* Docker
* Docker Compose
* Linux
* GPU Workers

Authentication

* Self-hosted Supabase
* JWT
* RBAC

AI Providers

* AudioCraft
* Amphion
* OpenVoice
* RVC
* ComfyUI
* Future AI Providers

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Core Responsibilities:

Design and implement a Modular AI Gateway (FastAPI) using an Adapter Pattern.
Setup and manage GPU Worker Architecture (using RunPod or similar GPU providers).
Implement an Orchestration Layer (Celery/Redis) for asynchronous job processing.
Build a scalable backend capable of handling Multi-tenancy and Enterprise SDKs.
Ensure clean architecture (Routers, Services, Repositories).
Document the entire infrastructure for future maintainability.
Technical Stack Requirements:
Backend: Python (FastAPI).
Database/Auth: Supabase.
Queueing: Redis/Celery.
Infrastructure: Docker, GPU Orchestration (RunPod), Cloud Infrastructure.
AI Exposure: Experience with AudioCraft, RVC, Coqui TTS, or similar frameworks is a plus.

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# What We Expect

We are looking for someone who can think like a Platform Architect and build clean, maintainable systems.

The architecture must remain:

* Provider Independent
* Model Agnostic
* Multi-Tenant
* White-label Ready
* Enterprise Ready
* Scalable
* Secure

Business logic must never depend on a specific AI provider.

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# Required Skills

Strong experience with:

* Python
* FastAPI
* PostgreSQL
* Redis
* Celery
* Docker
* Linux
* REST API Design
* Background Workers
* Authentication & Authorization
* Enterprise SaaS Development

Experience with AI model integration is highly preferred.

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Experience with:

* AudioCraft
* Amphion
* OpenVoice
* RVC
* ComfyUI
* GPU Infrastructure
* CUDA
* RunPod or other GPU cloud providers
* AI Media Pipelines

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# Project Status

The project architecture has already been designed.
Documentation already exists for:

* Engineering Constitution
* Software Architecture
* Database Architecture
* Master Roadmap
* Development Standards
* Security Architecture
* AI Platform Architecture

we have a "Serverless" NVIDIA account in runpod

You will implement the platform based on these documents.

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# Important Technical Question

Please explain how you would build an enterprise AI platform that supports:

* Multiple AI providers
* Provider-independent architecture
* Multi-tenancy
* White-label
* Credits
* Feature-based subscriptions
* Background AI job processing
* SDKs
* Future AI provider integrations