Developer Backend AI Driven Ad Platform Python / Django

We are looking for a Senior Backend Developer with deep expertise in Python/Django and hands-on experience integrating complex APIs in the digital advertising domain. You will be responsible for building the core backend logic of our AI-driven campaign platform, including full-cycle ad automation, real-time data synchronization, and scalable API infrastructure. Responsibilities: Ad Campaign Automation: Create, duplicate, update, and cancel campaigns in real time via Meta Ads, TikTok Ads, Google Ads, and YouTube Ads APIs. User Config & Permissions: Manage ad account connections, token storage (OAuth2), auto-refresh, and role-based access. AI-Powered Chat Backend: Build GPT-style backend for user interactions, including history, context, and multilingual support (i18n). Data Scraping & External Feeds: Extract and process data from external websites (BeautifulSoup, Selenium, Playwright). AI Integrations: Connect with OpenAI / Stable Diffusion for creative generation (text & image). Reporting & Analytics: Provide APIs for dashboards with real-time campaign performance, forecasts, and alerting (budget caps, milestones). Performance & Scalability: Develop distributed architecture with Celery/Redis, asynchronous tasks, caching, and load optimization. Security & Compliance: Ensure GDPR compliance, full encryption, logging, and audit trail. Requirements: 5+ years with Python, Django, Django Rest Framework. Proven experience with Meta Ads API, TikTok Ads API, Google Ads API (including OAuth2). Strong knowledge of PostgreSQL at scale. Experience with Celery/Redis for background processing. WebSockets (Django Channels) for chat/real-time events. Secure, scalable API design (rate limiting, throttling, monitoring). Role-based access control (RBAC) implementation. Web scraping with BeautifulSoup, Selenium, or Playwright. Hands-on experience with AI APIs (OpenAI, Stable Diffusion). Nice to Have: Docker, CI/CD pipelines (GitHub Actions/GitLab). Experience with AWS/GCP (servers, storage, Kubernetes). Background in digital marketing or ad tech. Familiarity with GraphQL APIs. 1. Data ingestion layer - Stream campaign performance metrics from Meta, Google, TikTok, and Youtube Ads APIs into a centeral warehouse(AWS + Postres/Redshift) 2. Real-time processing - use Celery + Redis for task queues, and Websockets for streaming performance updates. 3. AI optimization engine - Train models(PyTorch/TensorFlow) for predictive budget allocation and bid adjustments, factoring in CTR, ROAS, and conversions. 4. Decision execution - automatically push budget changes and campaign updates back to the APIs in real time In addition to the backend and AI optimization engine, our platform also includes a chat module for competitor analysis. The AI system should be able to provide better campaign results on Google and Meta by learning from competitor performance and benchmarks, while for TikTok the optimization needs to be based on their recommendation algorithm and engagement patterns. This means the AI must not only optimize based on CTR/ROAS but also factor in competitor strategies and platform-specific behaviors to give our users a real competitive edge. Cheak all information And share with me your most successful AI projects, especially ones that demonstrate advanced backend and optimization capabilities. It’s very important for us that you have real experience in developing campaign management systems (integrating with ad platforms, handling budgets, optimization, AI-driven automation). This project requires the highest level of expertise, so I’d like to see concrete examples of your past work.

Project ID: 39754845