oracle
Staff Software Developer
Fortinet Inc.
Santa Clara, USA
Full-time
Senior Level
Hybrid
USD 179000-219000 yearly
Discovered 1 weeks ago
Free
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Join Fortinet, a cybersecurity pioneer with over two decades of excellence, as we continue to shape the future of cybersecurity and redefine the intersection of networking and security.
At Fortinet, our mission is to safeguard people, devices, and data everywhere.
FortiSASE team is looking for a highly motivated full stack software engineer who can thrive in a fast pace environment and successfully contribute to the team.
The ideal candidate will have a can-do attitude, passion for technology, extensive development experience, and will be able to learn quickly.
Job Responsibilities
- Design, build, and enhance the FortiSASE platform, focusing on scalability, reliability, and the integration of AI-driven features.
- Work collaboratively with engineering teams and cross-functional product groups to architect, develop, and maintain core product capabilities.
- Innovate with team members to develop new solutions, including AI/ML applications, across areas such as network security configuration, telemetry analytics, data persistence, and RESTful API design.
- Research and evaluate emerging technologies, particularly in AI and automation, and drive their adoption into the product where appropriate.
- Collaborate with operations teams to diagnose, troubleshoot, and resolve issues in staging and production environments using modern observability and AI-assisted tools.
Job Requirements
- 5+ years of software development experience in the network and/or cloud security domain.
- Strong programming expertise in Python and Golang, with the ability to build scalable and maintainable systems.
- Hands-on experience with containerization and orchestration technologies, including Kubernetes, Docker, and Docker Compose.
- Deep knowledge of network telemetry pipelines, leveraging technologies such as Kafka and time-series databases, with experience applying AI/ML techniques for anomaly detection, predictive analytics, or intelligent alerting.
- Familiarity with modern AI development tooling and workflows, such as data pipelines, feature engineering, model deployment, monitoring, and MLOps practices.
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