Phoenix - Your AI AssistantFinalising a security platform
- Posted:
- Proposals: 18
- Remote
- #4418144
- OPPORTUNITY
- Awarded
Zurich 
Description
Experience Level: Expert
Project Scope
The role involves transforming the MVP into a full-scale platform ready for enterprise adoption, with strong frontend, backend, integrations, and deployment architecture.
Core Objectives
Restructure and optimize the existing MVP codebase.
Implement scalable frontend & backend architecture.
Integrate advanced fraud prevention and KYC systems.
Implement Trust Scoring & Escrow functionalities.
Ensure AI/ML model integration for fraud detection.
Set up infrastructure for scalability, security, and reliability.
Deploy to production-ready cloud infrastructure (AWS, GCP, or Azure).
Technical Requirements
1. Codebase & Architecture
Refactor MVP code for maintainability and scalability.
Enforce modular architecture (microservices or well-structured monolith).
Set up CI/CD pipelines (GitHub Actions / GitLab CI / CircleCI).
2. Frontend
Redesign UI for enterprise-grade look & feel (can collaborate with UI/UX designer).
Build responsive interfaces (React.js / Next.js / TailwindCSS).
Implement dashboard views:
Fraud Detection Dashboard
Trust Score Reports
Escrow & Transaction Tracking
Compliance & Audit Logs
3. Backend
Secure API development (Node.js / Python / Go).
Database design (PostgreSQL or MongoDB).
User & business onboarding workflows.
Integration with third-party KYC/AML providers (e.g., Onfido, Sumsub, Trulioo).
Fraud detection rules engine.
AI/ML model integration (TensorFlow / PyTorch models).
Escrow & payments integration (Stripe Connect, Payoneer, or equivalent).
4. Infrastructure & Hosting
Deploy on AWS / GCP / Azure.
Kubernetes or Docker containerization for scalability.
Secure configuration with IAM, VPC, encryption, firewalls.
Monitoring & logging (Datadog / Prometheus / ELK stack).
5. Security & Compliance
Implement role-based access control (RBAC).
GDPR & PCI-DSS compliance features.
End-to-end encryption for sensitive data.
Regular penetration testing & vulnerability scanning.
6. Deployment & Delivery
Staging, QA, and Production environments.
Automated testing (unit, integration, regression).
Scalable deployment pipelines.
The role involves transforming the MVP into a full-scale platform ready for enterprise adoption, with strong frontend, backend, integrations, and deployment architecture.
Core Objectives
Restructure and optimize the existing MVP codebase.
Implement scalable frontend & backend architecture.
Integrate advanced fraud prevention and KYC systems.
Implement Trust Scoring & Escrow functionalities.
Ensure AI/ML model integration for fraud detection.
Set up infrastructure for scalability, security, and reliability.
Deploy to production-ready cloud infrastructure (AWS, GCP, or Azure).
Technical Requirements
1. Codebase & Architecture
Refactor MVP code for maintainability and scalability.
Enforce modular architecture (microservices or well-structured monolith).
Set up CI/CD pipelines (GitHub Actions / GitLab CI / CircleCI).
2. Frontend
Redesign UI for enterprise-grade look & feel (can collaborate with UI/UX designer).
Build responsive interfaces (React.js / Next.js / TailwindCSS).
Implement dashboard views:
Fraud Detection Dashboard
Trust Score Reports
Escrow & Transaction Tracking
Compliance & Audit Logs
3. Backend
Secure API development (Node.js / Python / Go).
Database design (PostgreSQL or MongoDB).
User & business onboarding workflows.
Integration with third-party KYC/AML providers (e.g., Onfido, Sumsub, Trulioo).
Fraud detection rules engine.
AI/ML model integration (TensorFlow / PyTorch models).
Escrow & payments integration (Stripe Connect, Payoneer, or equivalent).
4. Infrastructure & Hosting
Deploy on AWS / GCP / Azure.
Kubernetes or Docker containerization for scalability.
Secure configuration with IAM, VPC, encryption, firewalls.
Monitoring & logging (Datadog / Prometheus / ELK stack).
5. Security & Compliance
Implement role-based access control (RBAC).
GDPR & PCI-DSS compliance features.
End-to-end encryption for sensitive data.
Regular penetration testing & vulnerability scanning.
6. Deployment & Delivery
Staging, QA, and Production environments.
Automated testing (unit, integration, regression).
Scalable deployment pipelines.
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Log inClarification Board Ask a Question
-
Hi Michael,
The project scope is quite extensive, involving enterprise-grade architecture, AI/ML fraud detection, KYC integrations, and cloud deployment, which typically require significant development time and resources. Could you please clarify if £250 is just for an initial milestone or proof-of-concept, or if it’s intended to cover the full build?
Thanks
Naresh