What are the responsibilities and job description for the Security Architect AI position at Cygnus Professionals Inc.?
Overview
seeking a Senior AI Security Technical Architect to continue to build upon a defined enterprise AI security strategy, ensuring artificial intelligence and generative AI capabilities are designed, deployed, and operated in a secure, compliant, and responsible manner.
This role is responsible for aligning business objectives, technology strategy, and security architecture to enable AI innovation with clear guardrails. The Senior AI Security Technical Architect will establish standards, patterns, and governance across multiple AI usage models, including third-party SaaS AI solutions, internally developed AI/ML platforms, and emerging agentic and autonomous AI systems.
By grounding AI security practices in industry frameworks such as NIST AI Risk Management Framework (AI RMF) and MITRE ATLAS, this role ensures AI risks are proactively identified, communicated, and mitigated while supporting the firm’s broader digital transformation, cloud adoption, and regulatory obligations.
What You’ll Do
• Own and evolve the enterprise AI security architecture and strategy, aligning business goals, technology platforms, and risk management practices.
• Assist in defining secure-by-design patterns and standards for AI/ML systems
• Establish and maintain AI-specific security artifacts
• Ensure consistent adoption of NIST AI RMF, MITRE ATLAS, CIS, ISO 27001 across AI initiatives.
• Establish architectural governance and enforce adherence to AI security standards across product teams and platforms.
• Influence AI design decisions early in the lifecycle to reduce downstream risk and rework.
• Partner with enterprise stakeholders to balance speed of innovation with risk tolerance and regulatory expectations.
• Evaluate AI frameworks, agents, vector databases, and third-party AI platforms for security posture and enterprise readiness.• Recommend and rationalize AI security tooling as part of the broader enterprise
security strategy.
• Monitor emerging AI threats, regulatory guidance, and industry best practices to inform security strategy and standards.
What Experience You’ll Need
• Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience.
• 8–12 years of experience in cybersecurity engineering or architecture within a complex enterprise environment.
• 2–4 years of hands-on experience securing or reviewing AI/ML systems and platforms.
• Strong understanding of:
o LLM architectures, embeddings, and Retrieval-Augmented Generation (RAG) patterns
o End-to-end ML pipelines (training → validation → deployment → inference)
o AI model supply chain risks (model registries, containers, dependencies, open-source components)
o Zero Trust and identity-centric security models
o Cloud security across Azure, AWS, and GCP
• Proven ability to influence architecture decisions and lead cross-functional initiatives at the enterprise level.
- • Excellent communication skills, with the ability to engage senior technical and business leaders.