Rakuten Advertising Tech Stack
Affiliate and partner marketing platform with AI-backed performance analytics
Rakuten Advertising operates an affiliate marketing network backed by AI and large-scale data infrastructure. The stack reveals a maturing engineering organization: Kubernetes and Terraform for orchestration, BigQuery and Pub/Sub for event streaming and analytics, and recent adoption of Claude/ChatGPT plus LangChain/AutoGen for model development. Active hiring skews toward junior and intern-level engineers alongside sales roles, suggesting either team expansion or high turnover in execution-focused positions. Internal pain points center on client profitability, risk mitigation, and post-launch implementation issues—typical friction points in a performance-marketing platform serving multiple constituencies.
Tech Stack 17 technologies
What Rakuten Advertising Is Building
◆Challenges
- Increasing client profitability
- Reducing risk
- Meeting aggressive revenue goals
- Post-launch implementation issues
- Online advertising ecosystem challenges
- Client satisfaction
- Employee relations risk
- Visa application processing
- Hris data inconsistencies
- Temporary staffing gap
▲Active Projects
- Cse elections implementation
- Affiliate marketing program
- In-house ml model development
- Scalable model deployment
- Visa application processing
- Hr data trend analysis
- Update local policies
- Maintain employee handbooks
- New customer acquisition for affiliate marketing channel
- Represent at trade shows
