Multi-Region SaaS Backend Optimization (Django + Kubernetes + Cloud | Long-Term Opportunity)

We are building a multi-region, compliance-focused SaaS architecture for healthcare systems where data must remain within country boundaries (India, US, UAE).

The system is already partially implemented and running across multiple environments using a hub (control plane) + regional pods (data planes) architecture. We are now expanding and refining critical components.

We are looking for an experienced backend/cloud engineer to help with:

* Improving onboarding and routing logic across regions
* Strengthening API security (token handling, session validation, encryption flow)
* Optimizing database performance (avoiding N+1 queries, improving query patterns)
* Ensuring consistency across multi-environment deployments
* Debugging real-world production issues across distributed systems

Tech stack includes:

* Django + DRF
* PostgreSQL
* Redis
* Azure (Blob Storage, Key Vault, AKS)
* Docker-based deployments

The architecture follows a control plane → data plane model, where:

* A central hub handles authentication and routing
* Regional pods handle all business logic and data

We are currently facing challenges around:

* Cross-region routing accuracy
* Secure token exchange between systems
* Maintaining performance under distributed workloads

Note:
This is not a basic CRUD project. If you have not worked with distributed systems, multi-region setups, or production-grade APIs, this may not be a good fit.

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Future Scope (Important)

This is part of a larger system we are actively building. There will be opportunities to work on:

* Multi-cloud expansion (AWS / Azure hybrid)
* Infrastructure automation (Terraform-based provisioning)
* Scaling and observability improvements
* Additional modules and region deployments

We are looking for someone interested in long-term collaboration, not just a one-time task.

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When applying, include:

1. Your experience with multi-region or distributed systems
2. Any work involving cloud infrastructure or backend scaling
3. How you approach debugging production-level issues

Shortlisted candidates will be given more detailed context and specific tasks.