Senior Software Developer - QMTC

Design, build, and ship features end-to-end across the frontend and backend of our AI-driven products — technical design, implementation, deployment, monitoring, and iteration — moving fluidly across the stack as needs shift Integrate AI/LLM capabilities into product workflows — chat, automation, personalization, and agentic flows that complete tasks end-to-end (booking, rescheduling, account changes) — as we move further into self-service Build, train, and evaluate applied ML models — forecasting, classification, or recommendation — that power predictive and recommendation features across our product line, going beyond LLM/API integration Build, maintain, and debug the data pipelines that feed our AI products — ingestion, transformation, and data quality checks across a medallion (bronze/silver/gold/platinum) architecture Join client and stakeholder conversations — demos, product launches, requirements discussions, troubleshooting calls — and translate customer and partner feedback into concrete product and engineering decisions, working closely with Product Management Write clean, maintainable, well-tested code, and help define architecture, patterns, and technical direction for new products as they take shape, rather than inheriting one fixed stack Support and troubleshoot production issues, including client-facing incidents when needed • 3+ years of professional experience building and shipping fullstack web applications, with strong engineering fundamentals independent of AI-assisted tooling • Strong hands-on experience across the stack: JavaScript/TypeScript (React or Vue, Node.js), a backend language suited to services and APIs (e.g. Python, Java, or similar), API design, and relational databases — comfortable with how frontend and backend fit together in production • Experience with cloud platforms (Azure, AWS, or Google Cloud), including building cloud data pipelines and ETL across a medallion (bronze/silver/gold/platinum) architecture • Real, hands-on experience building with AI/LLM capabilities in production — able to point to AI-driven features you’ve actually shipped (e.g. RAG pipelines, vector databases, or other LLM-adjacent infrastructure), not just curiosity about AI. Comfortable using AI coding tools day-to-day (e.g. Claude, Cursor, GitHub Copilot) • Genuine applied ML experience, distinct from LLM/API integration — has trained, fine-tuned, or evaluated models (e.g. classification, regression, or forecasting) and can reason about data qua

• 3+ years of professional experience building and shipping fullstack web applications, with strong engineering fundamentals independent of AI-assisted tooling • Strong hands-on experience across the stack: JavaScript/TypeScript (React or Vue, Node.js), a backend language suited to services and APIs (e.g. Python, Java, or similar), API design, and relational databases — comfortable with how frontend and backend fit together in production • Experience with cloud platforms (Azure, AWS, or Google Cloud), including building cloud data pipelines and ETL across a medallion (bronze/silver/gold/platinum) architecture • Real, hands-on experience building with AI/LLM capabilities in production — able to point to AI-driven features you’ve actually shipped (e.g. RAG pipelines, vector databases, or other LLM-adjacent infrastructure), not just curiosity about AI. Comfortable using AI coding tools day-to-day (e.g. Claude, Cursor, GitHub Copilot) • Genuine applied ML experience, distinct from LLM/API integration — has trained, fine-tuned, or evaluated models (e.g. classification, regression, or forecasting) and can reason about data quality, features, and model performance, not just prompted a hosted model • Excellent communication skills — able to explain technical concepts clearly to clients, partners, and non-technical stakeholders, and comfortable in customer-facing settings (demos, calls, workshops) • A flexible, product-minded, and collaborative approach — curious and accountable, comfortable moving between products and technologies as our portfolio grows rather than staying fixed to one stack, and taking initiative across teams • Fluent in written and spoken English • Reliable and deadline-driven — sets realistic estimates, hits them, and raises risk early when a date won’t be met • An active GitHub profile or portfolio of personal/side projects — evidence of hands-on engagement with the craft beyond day-to-day work Nice To Have • Exposure to Java, Spring, or Spring Boot (useful for interoperating with our existing legacy platform) • Exposure to generative avatar or video rendering for chat- and kiosk-based interfaces • Familiarity with speech-to-text or transcription pipelines, including multilingual voice input • Familiarity with agent orchestration frameworks or multi-step tool-use patterns • Experience with Go, used in some of our AI backend services What We Offer • The chance to help shape Qmatic’s next generation of AI-driven products, not ma

• The chance to help shape Qmatic’s next generation of AI-driven products, not maintain someone else’s roadmap • Direct exposure to clients and stakeholders across retail, finance, healthcare, and the public sector • A flexible working environment • A collaborative, innovative team culture • Professional development and learning opportunities

Aspire Software is looking for a Senior Software 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 Role We’re looking for a mid-to-senior Fullstack Developer to join the team building Qmatic’s next generation of AI-driven products. Unlike a role scoped to a single platform, this one is deliberately broad: moving between frontend, backend, and AI/ML integration work as the roadmap evolves. You’ll spend time close to the product itself — building features, wiring up integrations, shaping how AI shows up across the customer journey — and close to the people who use and sell it: product managers, sales teams, partners, and sometimes the end customer directly. This role sits at the intersection of engineering and business. You’ll join demos, translate technical trade-offs into plain language for non-technical stakeholders, and bring feedback from the field back into how we build. In practice that spans the data and retrieval work behind our chat product’s knowledge base, and the agentic, self-service capabilities we’re building next — letting customers complete a task end-to-end rather than just getting an answer. Responsibilities Design, build, and ship features end-to-end across the frontend and backend of our AI-driven products — technical design, implementation, deployment, monitoring, and iteration — moving fluidly across the stack as needs shift Integrate AI/LLM capabilities into product workflows — chat, automation, personalization, and agentic flows that complete tasks end-to-end (booking, rescheduling, account changes) — as we move further into self-service Build, train, and evaluate applied ML models — forecasting, classification, or recommendation — that power predictive and recommendation features across our product line, going beyond LLM/API integration Build, maintain, and debug the data pipelines that feed our AI products — ingestion, transformation, and data quality checks across a medallion (bronze/silver/gold/platinum) architecture Join client and stakeholder conversations — demos, product launches, requirements discussions, troubleshooting calls — and translate customer and partner feedback into concrete product and engineering decisions, working closely with Product Management Write clean, maintainable, well-tested code, and help define architecture, patterns, and technical direction for new products as they take shape, rather than inheriting one fixed stack Support and troubleshoot production issues, including client-facing incidents when needed • 3+ years of professional experience building and shipping fullstack web applications, with strong engineering fundamentals independent of AI-assisted tooling • Strong hands-on experience across the stack: JavaScript/TypeScript (React or Vue, Node.js), a backend language suited to services and APIs (e.g. Python, Java, or similar), API design, and relational databases — comfortable with how frontend and backend fit together in production • Experience with cloud platforms (Azure, AWS, or Google Cloud), including building cloud data pipelines and ETL across a medallion (bronze/silver/gold/platinum) architecture • Real, hands-on experience building with AI/LLM capabilities in production — able to point to AI-driven features you’ve actually shipped (e.g. RAG pipelines, vector databases, or other LLM-adjacent infrastructure), not just curiosity about AI. Comfortable using AI coding tools day-to-day (e.g. Claude, Cursor, GitHub Copilot) • Genuine applied ML experience, distinct from LLM/API integration — has trained, fine-tuned, or evaluated models (e.g. classification, regression, or forecasting) and can reason about data quality, features, and model performance, not just prompted a hosted model • Excellent communication skills — able to explain technical concepts clearly to clients, partners, and non-technical stakeholders, and comfortable in customer-facing settings (demos, calls, workshops) • A flexible, product-minded, and collaborative approach — curious and accountable, comfortable moving between products and technologies as our portfolio grows rather than staying fixed to one stack, and taking initiative across teams • Fluent in written and spoken English • Reliable and deadline-driven — sets realistic estimates, hits them, and raises risk early when a date won’t be met • An active GitHub profile or portfolio of personal/side projects — evidence of hands-on engagement with the craft beyond day-to-day work Nice To Have • Exposure to Java, Spring, or Spring Boot (useful for interoperating with our existing legacy platform) • Exposure to generative avatar or video rendering for chat- and kiosk-based interfaces • Familiarity with speech-to-text or transcription pipelines, including multilingual voice input • Familiarity with agent orchestration frameworks or multi-step tool-use patterns • Experience with Go, used in some of our AI backend services What We Offer • The chance to help shape Qmatic’s next generation of AI-driven products, not maintain someone else’s roadmap • Direct exposure to clients and stakeholders across retail, finance, healthcare, and the public sector • A flexible working environment • A collaborative, innovative team culture • Professional development and learning opportunities