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Staff Security Engineer
Sin especificarTiempo completoSecurity EngineeringEnterprise Software
Join a founding Security R&D team building production-grade security capabilities for enterprise software. The role combines software engineering, security automation, AI integrations, and collaboration with product and AI security teams.
Responsabilidades
- Design and develop security tooling, automation, and platform services at enterprise scale.
- Contribute security capabilities directly to product engineering codebases.
- Build AI-powered security automation by integrating internal models and third-party services into production workflows.
- Use platform runtime, access-control, data-layer, and workflow capabilities to develop security solutions.
- Collaborate with AI security researchers to turn research into production-grade engineering.
- Partner with product engineering teams through code contributions, design reviews, code reviews, and architecture discussions.
- Establish engineering practices, technical standards, and team foundations as a founding member.
- Support hiring and onboarding as the team grows.
- Track emerging AI/ML technologies and security threats to inform the team roadmap.
Requisitos
- At least 8 years of professional software engineering experience building production systems at scale.
- Bachelor’s degree in computer science, engineering, or a related technical field.
- Strong production experience with Python and Java.
- Knowledge of distributed systems, cloud-native architectures, scalability, reliability, and performance engineering.
- Experience contributing to shared codebases in collaborative engineering environments.
- Interest in security engineering, including application security, infrastructure security, identity systems, or trust and safety.
- Curiosity about AI/ML and emerging AI technologies.
Se valora
- Experience developing security tooling, SSDLC automation, or product security features.
- Familiarity with containers, Kubernetes, cloud security, or infrastructure as code.
- Exposure to AI/ML pipelines, LLM integrations, or agentic frameworks.
- Experience with SaaS or platform companies building multi-tenant enterprise software.
- Experience working in globally distributed engineering teams.