Job Description

Aspire Software is looking for a AI Product Engineer 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.

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 code
• Generate unit/integration tests
• Create migration scripts
• Perform static analysis and code reviews
• Produce technical documentation
• Build internal AI assistants for:
• Log analysis
• Support ticket triage
• Codebase navigation
• Technical debt discovery

• Continuously 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:
• NET
• C#
• ASP.NET Web APIs

Solid understanding of:

• Entity Framework / ORM patterns
• SQL and database design (MySQL/MariaDB experience preferred)
• Clean architecture principles
• Dependency injection
• Testing frameworks (xUnit, NUnit, etc.)

Java & Distributed Systems

• Professional experience with:
• Java (Spring ecosystem or similar preferred)
• Gradle or equivalent build tooling
• Experience working in microservices architectures.

Comfortable with:

• Linux command line environments
• Deployment automation (e.g., Ansible or similar)
• XML/CSV processing
• Automated testing tools (Selenium/Testim or similar)

Cloud & Data

• Azure experience preferred.
• Familiarity with:
• Databricks or Spark-based data pipelines
• Python-based data workflows (integration-level understanding)
• CI/CD pipelines.
• Infrastructure as Code familiarity.
• Observability (logging, tracing, monitoring).

AI & Automation

Hands-on experience with:

• LLM APIs
• Code copilots and AI IDE tooling
• Prompt engineering for engineering workflows

· Experience building:

• AI-assisted tools
• Internal bots or automation agents

Understanding of:

• Model limitations
• Cost-performance trade-offs
• Guardrails 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.