AI Software Engineer
Join Qargo as an AI Software Engineer and help build intelligent, user-centric AI features that reshape how modern logistics companies work - driving efficiency, automation, and real impact at scale.
🚛 About Qargo
Qargo is a cloud-based (SaaS) Transport Management Platform. We are a scale-up based in London and Ghent (Belgium), rapidly expanding across Europe. The platform is an ‘all-in-one system’, handling everything from initial order entry to final invoicing. It optimises planning and has many built-in AI features to automate routine manual tasks and help spot potential issues. Qargo is designed to help modern logistics operations run more efficiently, while increasing profitability and sustainability.
We’re looking for an AI Software Engineer to join our team in Ghent. If you’re looking to work in an international company in a role that offers autonomy, ownership and impact, this is the role for you!
💼 About the Role
We are constantly looking for ways to save transport companies time and prevent planning and administrative errors using AI. We use an iterative approach: start with a small MVP (minimum viable product) that aids the user, then further automate based on user feedback. As an AI engineer, you must learn to think like the user and understand what truly helps them save time and reduce mistakes.
- You will work across research, rapid prototyping, and productionisation of AI features.
- Your focus will be on applying and integrating state-of-the-art models (LLMs, vision, document understanding) into Qargo’s platform.
- You will collaborate closely with engineering and product teams to turn real logistics challenges into practical AI solutions.
- You will help scale, monitor, and improve our AI components to ensure reliability, efficiency, and performance.
- You will contribute to shaping Qargo’s long-term AI strategy and roadmap.
🔑 Key Responsibilities
- Evaluate and prototype with new AI models and techniques to solve document, workflow, and conversational tasks.
- Bring AI prototypes to production, ensuring quality, scalability, and observability.
- Monitor and maintain AI systems running in production, optimising cost, latency, and reliability.
- Collaborate with cross-functional teams to define clear AI tasks (e.g., document classification, summarisation, task prediction).
- Develop and enhance AI-driven features such as document extraction, matching flows, quality checks, chatbots, and automated bookings.
- Stay up to date with advancements in AI and identify opportunities to improve the product.
✅ Skills & Experience
- Min. 2 years of experience in software engineering, applied AI, or similar technical roles.
- Strong programming skills (preferably Python and/or modern backend languages).
- Experience with AI/ML tools and frameworks such as PyTorch, Hugging Face, LangChain/LangGraph, vector databases, and inference tooling.
- Proven experience deploying and operating AI/ML systems in a production environment.
- Ability to experiment quickly, iterate fast, and validate assumptions.
- Strong problem-solving skills and the ability to work autonomously in a fast-paced environment.
- Clear communication skills and the ability to collaborate with engineers, product managers, and domain experts.
- Experience with document processing, NLP, or conversational AI is a plus.
🤝 What We Offer
- Real impact and ownership in a growing international scale-up
- A supportive and collaborative team culture
- Hybrid working setup with flexibility and trust
- Opportunities to learn, grow, and expand your technical knowledge
- Competitive salary and benefits package
- Department
- Engineering
- Role
- Software Engineer
- Locations
- Ghent
- Remote status
- Hybrid
About Qargo
Qargo is a tech scale-up with offices based in London and Ghent. We are on a mission to transform the transportation industry by making it more efficient, profitable, and sustainable. Together we are building the most user-friendly and intuitive Transport Management System (TMS) on the market that automates administrative processes and optimizes planning.