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Ethos Life is a leading life insurance technology company democratizing access to life insurance through a three-sided platform serving consumers, agents, and carriers. The company offers instant, accessible products with no medical exams and a seamless online process.
You will join as Principal Security Engineer reporting directly to the CISO, leading the design and implementation of scalable, secure systems across cloud platforms and modern application stacks, including AI-powered tooling. This high-impact role shapes the security posture of platforms and development practices while working across engineering, DevOps, architecture, and compliance teams.
Core responsibilities include designing and implementing secure architectures for applications, APIs, microservices, and containerized workloads; developing and enforcing application security best practices across the SDLC; conducting threat modeling and security design reviews; evaluating and implementing security tools and controls; providing technical leadership and mentorship to security engineers and developers; leading complex incident response and root cause analysis; and staying current with emerging threats and security technologies.
You will own the AI security program, including risk frameworks, threat models, and governance policies for AI/ML systems and LLM integrations. This includes reviewing new AI tool features for security risks (prompt injection, data leakage, model poisoning, supply chain threats), tracking industry guidance from NIST AI RMF and OWASP LLM Top 10, embedding AI security reviews into feature development, and monitoring AI regulatory developments.
Required: 10+ years in security engineering or architecture; Bachelor's in Cybersecurity, IT, or Computer Science; deep expertise in AWS and infrastructure-as-code (Terraform, CloudFormation); strong application security experience (OWASP Top 10, SAST, DAST, threat modeling); experience with zero-trust architectures and identity/access controls; proficiency in Python, Go, or JavaScript; demonstrated leadership in cross-functional initiatives; hands-on experience assessing AI/ML security risks; and ability to evaluate AI tools for security implications.
Preferred: CISSP, CCSP, or AWS Security Specialty certifications; Kubernetes and cloud-native security experience; background in regulated industries (fintech, healthcare); AI red-teaming or adversarial ML experience; and knowledge of emerging AI regulatory frameworks.
