AI Automation Engineer - VCTS at Valsoft Corporation

Beirut, Beirut Governorate, Lebanon -

Full Time

Start Date

Immediate

Expiry Date

24 Jun, 26

Salary

0.0

Posted On

26 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Javascript, Typescript, Java, Go, CI/CD, Docker, LLM, LangChain, AutoGen, CrewAI, Semantic Kernel, Terraform, Ansible, Grafana, VictoriaMetrics

Industry

Financial Services

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. About theAI-Driven Automation Design and implement AI-powered automation workflows for development, testing, and operations. Develop and maintain AI-assisted testing systems, including test generation, failure analysis, and intelligent test selection. Build and orchestrate agent-based automation tools for operational and engineering tasks. Test Automation & Quality Engineering Develop and maintain automated test frameworks for APIs, services, and user interfaces. Integrate automated testing into CI/CD pipelines. Implement quality gates and automated validation across the software delivery pipeline. Analyze test results and production telemetry to continuously improve test coverage. DevOps & Infrastructure Automation Build and maintain CI/CD pipelines to support automated build, test, and deployment workflows. Automate infrastructure provisioning and environment setup using Infrastructure as Code. AI Tooling Integration Integrate LLM-based tools into developer workflows for: automated code review test case generation incident diagnostics documentation generation Evaluate and adopt emerging AI automation platforms and frameworks. Observability & Reliability Implement monitoring and observability for automation systems. Use telemetry and metrics to improve system reliability and automation effectiveness. Bachelor’s degree in Computer Science, Software Engineering, or related field, or equivalent experience. Experience in software development and automation engineering. Strong programming skills in at least one language such as: Python, JavaScript / TypeScript, Java, Go Experience building test automation frameworks. Experience working with CI/CD systems (e.g., GitHub Actions, GitLab CI, Jenkins). Familiarity with containerization technologies such as Docker. Understanding of software quality engineering principles. Preferred Qualifications Experience integrating AI/LLM technologies into engineering workflows. Familiarity with agent orchestration frameworks (e.g., LangChain, AutoGen, CrewAI, Semantic Kernel). Experience with cloud platforms (Azure). Knowledge of infrastructure as code (Terraform, Ansible, or similar). Experience with observability platforms (VictoriaMetrics, Grafana). Key Competencies Automation mindset and systems thinking Strong debugging and problem-solving skills Ability to design scalable automation architectures Curiosity for emerging AI and developer productivity tools Cross-functional collaboration with engineering and operations teams Example Deliverables An AI Automation Engineer may be responsible for building systems such as: AI-generated automated test suites Intelligent CI pipelines that adapt test execution based on code changes Agent-based incident investigation tools AI-assisted release validation pipelines Autonomous environment diagnostics

Responsibilities

This role involves designing and implementing AI-powered automation workflows for development, testing, and operations, including building and orchestrating agent-based automation tools for engineering tasks. Key duties also include developing automated test frameworks, integrating testing into CI/CD pipelines, and integrating LLM-based tools into developer workflows.