Security Architect (Superhive)

About UsAI71 is an applied research team dedicated to creating helpful and responsible AI agents for knowledge workers.Working closely with our industry partners, our cross-functional teams of AI experts build products grounded in the cutting edge research of our colleagues from the Technology Innovation Institute (TII).We are seeking a highly experienced and strategic Security Architect to define and lead the security architecture of our AI and data platform. In this role, you will be responsible for designing secure-by-design systems across AI workloads, data pipelines, and cloud-native infrastructure, ensuring the confidentiality, integrity, and availability of our platform at scale.You will collaborate closely with engineering, platform, and AI teams to embed security into every layer of system design, development, and deployment, while establishing standards and best practices aligned with enterprise and high-security environments. Key ResponsibilitiesSecurity Architecture and Design • 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.Platform and Infrastructure Security • 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.AI and Data Security • 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.DevSecOps and Governance • Embed security into GitOps 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.Observability and Threat Detection • Define requirements for security observability, including audit logging and anomaly detection. • Ensure integration of security signals into observability platforms (e.g., OpenTelemetry).Leadership and Collaboration • 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.Qualifications Required Skills and Experience • 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 DevSecOps practices and secure CI/CD pipelines.Preferred Skills • 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.Why Join Us? • Work on cutting-edge AI technologies with a focus on security and ethics. • Shape the security architecture of a next-generation AI platform. • Collaborate with a diverse and talented team. • Competitive salary, equity options, and benefits. • Opportunities for growth and leadership. Show more Show less

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 DevSecOps practices and secure CI/CD pipelines.

Security Architecture and Design: 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. Platform and Infrastructure Security: 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. AI and Data Security: 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. DevSecOps and Governance: Embed security into GitOps 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. Observability and Threat Detection: Define requirements for security observability, including audit logging and anomaly detection. Ensure integration of security signals into observability platforms (e.g., OpenTelemetry). Leadership and Collaboration: 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.