AI Developer

Aspire Software is looking for a AI Developer to join our team in Lebanon.

Here is a little window into our company: Aspire Software operates and manages wholly owned software companies, providing mission-critical solutions across multiple verticals. By implementing industry best practices, Aspire delivers a time sensitive integration process, and the operation of a decentralized model has allowed it to become a hub for creating rapid growth by reinvesting in its portfolio.

About the job:

We're looking for an AI Developer to join Klopotek's engineering team from our Beirut office. You will work remotely alongside our development team in Gioia del Colle, Italy – designing, building and running AI-powered capabilities inside the software that runs the publishing operations of major global publishers.

This is a hands-on engineering role, not a research position. You will integrate large language models into production systems: retrieval over our product knowledge, AI assistants for support and operations, agentic workflows that act on real business data, and AI features inside our products. Our core platform is built on Java and Oracle, so you will work close to that stack – connecting AI services to existing APIs, data and business logic, and making them reliable, secure and measurable.

You will be joining a small but growing Klopotek team in Lebanon – four colleagues are already working with us from Beirut, and this role is part of a deliberate expansion of our engineering presence there. You'll have a genuine peer group locally, and work closely with the Italian development team day to day.

This is not a role that rewards knowing the right buzzwords. It is a role for someone who is selfdriven, technically grounded and genuinely excited about learning – someone who can tell a convincing prototype from a dependable product, and who takes ownership from idea through to production.

What You'll Do

• Design, build and run LLM-powered features and services – from first prototype to monitored production

• Build retrieval-augmented generation (RAG) pipelines over product documentation, configuration knowledge and support history: ingestion, chunking, embeddings, search and ranking

• Develop agentic workflows and tool integrations (e.g. via the Model Context Protocol) that let AI work safely with our APIs, ticketing systems and business data

• Integrate AI services with our Java backend services, REST APIs and Oracle databases

• Build evaluation suites and test sets so we know – with numbers – whether a change makes an AI feature better or worse