Offer summary

Qualifications:

Proven experience in AI architecture and development, particularly in cloud-native environments., Strong knowledge of AI/ML technologies and frameworks, including natural language processing and OCR., Familiarity with backend technologies such as PostgreSQL and Java., Experience in designing scalable and secure architectures for AI applications..

Key responsibilities:

Design and develop a cloud-native AI-first architecture for a fleet management platform.

Implement AI-powered document ingestion and search systems, including OCR capabilities.

Build a virtual AI assistant to handle fleet-related queries and tasks.

Collaborate with product managers and development teams to ensure effective integration of AI services.

Job description

The project

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 number of open vacancies: 1

Type of contract: B2B/Labour Contract
The preferred scale of work: full-time
Start date: June 2025, long-term cooperation
Type of work: 100% remote from Poland (Lublin preferred)

Location: Poland

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.