About this role
Aspire Software is looking for an intermediate 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.
Role Overview
We are hiring an AI-native software engineer who treats large language models, copilots, and agentic workflows as core parts of their development environment, not optional add-ons.
You will design, build, and refactor production systems in .NET/C#, while also contributing significantly to a mature Java-based distributed platform composed of multiple microservices and supporting data tooling.
You are not just a developer. You are an architect, systems thinker, and automation builder who can operate across stacks and reduce complexity over time.
What “AI-Native” Means Here
This is not just “comfortable with GitHub Copilot/Claude Code/Codex.” You:
Use AI daily to generate, refactor, test, document, and review code.Build internal AI agents and workflows to automate repetitive engineering tasks.Design systems assuming AI components will exist in the architecture.Know when AI is wrong and can spot hallucinations instantly.Continuously experiment with new tools and replace old workflows aggressively.
Responsibilities
1. Architect and Build Scalable Systems (.NET)
Design and implement high-quality backend systems in .NET and C#.Build modular, testable, maintainable architectures.Make sound trade-offs between performance, maintainability, and speed of delivery.Refactor legacy systems intelligently (not cosmetically).
2. Contribute to a Distributed Java Platform
Support and evolve a Java-based enterprise platform consisting of ~20 microservices.Work with a Java UI framework and REST-based service architecture.Maintain and enhance internal tooling for data mapping, validation, and automated query testing.Contribute to an authorization/security service layer.Interface with data generation pipelines built on Spark/Azure Databricks.Operate comfortably in Linux environments and deployment automation workflows.This portion of the role requires ownership mindset, production debugging capability, and comfort navigating distributed systems.
3. Leverage AI Across the SDLC
Use LLMs and code-generation tools to:Draft and refactor production codeGenerate unit/integration testsCreate migration scriptsPerform static analysis and code reviewsProduce technical documentationBuild internal AI assistants for:Log analysisSupport ticket triageCodebase navigationTechnical debt discoveryContinuously optimize development workflows using AI.
4. Own Architecture Decisions
Design APIs (REST, event-driven, microservices where appropriate).Work with cloud-native patterns (Azure preferred).Integrate AI services into production systems.Evaluate when to build vs. buy vs. automate.Improve observability, resilience, and service boundaries over time.
5. Raise the Bar
Set standards for AI-assisted development.Mentor other engineers in AI-native workflows.Push for measurable productivity gains.Eliminate manual processes wherever possible.
Requirements
Core Stack (.NET)
Strong experience with:.NETC#ASP.NET Web APIsSolid understanding of:
Entity Framework / ORM patternsSQL and database design (MySQL/MariaDB experience preferred)Clean architecture principlesDependency injectionTesting frameworks (xUnit, NUnit, etc.)
Java & Distributed Systems
Professional experience with:Java (Spring ecosystem or similar preferred)Gradle or equivalent build toolingExperience working in microservices architectures. Comfortable with:
Linux command line environmentsDeployment automation (e.g., Ansible or similar)XML/CSV processingAutomated testing tools (Selenium/Testim or similar)
Cloud & Data
Azure experience preferred.Familiarity with:Databricks or Spark-based data pipelinesPython-based data workflows (integration-level understanding)CI/CD pipelines.Infrastructure as Code familiarity.Observability (logging, tracing, monitoring).
AI & Automation
Hands-on experience with:
LLM APIsCode copilots and AI IDE toolingPrompt engineering for engineering workflows· Experience building:
AI-assisted toolsInternal bots or automation agentsUnderstanding of:
Model limitationsCost-performance trade-offsGuardrails and reliability
What We’re Looking For
Technical Depth
You can:
Read a large, multi-service codebase and map it quickly.Trace issues across services without getting lost.Identify architectural rot fast.Make systems simpler, not more complex.
AI Skeptic + Optimist
You:
Aggressively use AI but never blindly trust it.Know how to validate outputs.Treat AI as a junior developer that needs supervision.
Nice to Have
Experience modernizing legacy .NET Framework or Java systems.Experience improving reliability in distributed microservice environments.Exposure to Node.js / Express / modern frontend frameworks.Experience integrating AI into enterprise workflows.Background in regulated or compliance-heavy industries.