We are looking for an experienced AI Architect / Developer to design and develop a next-generation, AI-first fleet management platform built from the ground up with a cloud-native architecture. This is a greenfield opportunity for an innovator who thrives on building intelligent systems that scale, with a strong emphasis on leveraging AI to improve operational efficiency, driver safety, and compliance in fleet operations.

You will play a key role in driving technical strategy, designing core AI services, and implementing features including digital driver's license verification, AI-powered document search (OCR), natural language query support, and a virtual AI assistant.

Industry: Fleet management

Team: Tech Lead, Backend developers, QA (Poland and Egypt)
The preferred scale of work: full-time
Start date: June 2025, long-term cooperation
Type of work: Hybrid

Location: Maadi, Cairo, Egypt.

Main technologies used in the project:

• Frontend: Vaadin (mobile-first, responsive) 
• Backend: PostgreSQL (with JSON indexing) 
• Server: Tomcat (Java stack) 
• AI Services: TBC

Your tasks:

• Design and develop a cloud-native AI-first architecture.
• Ensure the architecture is modular, scalable, secure, and optimized for AI/ML workloads.
• Implement an AI-powered document ingestion and search system with support for OCR from scanned documents, and PDFs.
• Develop natural-language search functionality using LLMs (e.g., Google Document AI workbench) and prompt engineering techniques tailored to fleet management.
• Build a virtual AI assistant capable of understanding and responding to fleet-related queries and performing predefined tasks.
• Design and integrate a secure driver's license verification workflow, using image processing, validation APIs, and digital signatures.
• Define infrastructure as code (IaC) for scalable deployment across cloud providers (AWS).
• Define data pipelines for structured and/or unstructured data ingestion.
• Integrate third-party models or build custom AI/ML models for fleet-specific insights and automation.
• Work closely with product managers, Backend (Java) and Frontend developers.
• Provide guidance on AI best practices, model performance, and responsible AI use.