Security Architect

Key Responsibilities

• Define and evolve the end-to-end security architecture for AI systems, data platforms, and cloud-native infrastructure.
• Establish and enforce Zero Trust principles, including identity-first security, mTLS, and fine-grained access control (RBAC, ABAC).
• Design secure patterns for distributed systems, event-driven architectures, and multi-tenant environments.
• Define security standards for Kubernetes-based platforms, including workload isolation, network policies, and runtime protection.
• Establish container and software supply chain security practices, e.g., image scanning, SBOM, signing, and provenance.
• Design secure deployment architectures for both cloud and restricted air-gapped environments.
• Define and implement security controls for LLM-based applications, RAG pipelines, and data platforms.
• Establish safeguards against AI-specific threats such as data poisoning, model extraction, and data leakage.
• Embed security into Git Ops and CI/CD workflows, including policy-as-code and automated enforcement.
• Define and maintain secure SDLC practices aligned with ISO
  27001 and internal governance frameworks.
• Lead threat modeling, architecture reviews, and security validations.
• Define requirements for security observability, including audit logging and anomaly detection.
• Ensure integration of security signals into observability platforms, e.g., Open Telemetry.
• Act as a security advisor to engineering and AI teams.
• Review system designs and enforce security standards.
• Mentor engineers and promote a strong culture of security awareness.

• Bachelor's or Master's degree in Computer Science, Cybersecurity, or a related field.
• 7+ years of experience in security engineering, architecture, or related roles.
• Experience designing security for distributed systems and cloud-native platforms.
• Strong understanding of Zero Trust, IAM, cryptography, and secure communication.
• Experience with Dev Sec Ops  practices and secure CI/CD pipelines.

• Experience securing AI/ML systems or data platforms.
• Familiarity with streaming technologies (e.g., Kafka, NATS).
• Experience in regulated or high-security environments.
• Certifications such as CISSP or CSSLP.
• Proficiency in Python or Bash for automation.