Software Engineer, Autonomous Security

We are seeking a visionary Software Engineer to join our newly formed Autonomous Security team. This is not a traditional "monitor and patch" role. In this position, you will be at the forefront of the next evolution of cybersecurity: Autonomous (AI) Security Team.

Your mission will be to design, build, and deploy AI agents that act as autonomous security researchers and first responders. You will move our security posture from "Human-in-the-loop" to "Human-on-the-loop," creating a self-healing infrastructure that identifies, tests, and mitigates vulnerabilities at machine speed.

Responsibilities:

• AI Agent Development: Build and fine-tune LLM-based agents to perform automated vulnerability research and code analysis.
• Autonomous Remediation: Develop "self-healing" pipelines that automatically generate, test, and deploy security patches and dependency updates via Kargo and ArgoCD.
• Threat Mitigation: Design AI-driven logic to detect anomalous traffic patterns and autonomously update WAF rules or service mesh configurations to neutralize external threats in real-time.
• Pipeline Integration: Integrate AI security tooling directly into our CI/CD lifecycle, ensuring that security is an automated, invisible, and frictionless part of the development process.
• Security Orchestration: Build the "nervous system" that connects security scanning tools (Snyk, Wiz, etc.) with AI agents to prioritize and resolve alerts without manual triage.

Minimum Qualifications:

• Programming & Automation: 3+ years developing production software, backend services, or automated tooling using Python or Go.
• Cloud-Native & CI/CD: Hands-on experience containerizing applications, managing Kubernetes deployments, and building automated CI/CD or GitOps pipelines (e.g., ArgoCD, GitHub Actions, GitLab CI).
• Application Security: Demonstrated experience implementing secure coding practices, applying OWASP Top 10 mitigation strategies, and remediating CVEs in cloud environments.

Preferred Qualifications:

• AI/LLM Engineering: Practical experience integrating Large Language Model (LLM) APIs, structured prompt workflows, or agentic frameworks into software applications.
• Familiarity with vector databases (Pinecone, Milvus) for security context retrieval.
• Familiarity with "Policy as Code" (OPA/Rego).