Red hat Principal Full Stack Software Engineer - hybrid Raanana 

Israel, Center District, Raanana 

934878550

What You Will Do:

• Build and maintain full-stack applications that power model validation pipelines—from backend microservices to front-end dashboards.

• Develop clean, efficient APIs to automate model benchmarking, inference performance testing, and accuracy evaluation.

• Design user-friendly web interfaces that visualize model insights and validation results for both internal teams and external users.

• Contribute to CI/CD workflows for automated testing, deployment, and continuous integration of model validation tools.

• Work closely with platform engineers, DevOps specialists, and data scientists to ensure a seamless AI model lifecycle experience.

• Troubleshoot issues across the stack, improve performance, and ensure security and reliability across services.

• Actively participate in agile processes, sprint planning, and technical reviews, contributing to a collaborative, high-performing team culture.

• Share ideas that improve user experience, developer workflows, and validation system scalability.

What You Will Bring:

• Proficiency in front-end frameworks (e.g., React, Vue, or Angular ) and strong skills in HTML, CSS , and modern JavaScript/TypeScript

• Experience developing and maintaining backend microservices using Python, Go, Node.js, or similar languages

• Solid understanding of REST APIs, web architecture, and database design (SQL or NoSQL)

• Familiarity with CI/CD pipelines, GitOps workflows, and automated testing practices

• Comfort working across the stack, with an eagerness to contribute wherever needed

• Basic understanding of AI/ML workflows and MLOps (not required, but a plus)

• Strong debugging, troubleshooting, and communication skills

• Bachelor’s degree in Computer Science or related field, or equivalent practical experience

Nice to Have:

• Experience with containerization and orchestration tools like Docker and Kubernetes

• Knowledge of data visualization libraries (e.g., D3.js, Chart.js, Plotly)

• Exposure to AI model inference frameworks or data pipelines

• Contributions to open source or a passion for collaborative development