AI Security and Governance Architect - Lead Software Security Architect

Overview

AI Security and Governance Architect - Lead Software Security Architect

📍 Hyderabad / Remote 

About the Role

The AI Security and Governance Architect plays a critical role in safeguarding the company’s software, AI, and machine learning (ML) systems by ensuring secure design, ethical governance, and proactive risk management across the AI lifecycle. This position leads efforts to align AI development and deployment with both cybersecurity and regulatory frameworks, fostering a culture of responsible AI use and compliance.

You will collaborate closely with product, data science, compliance, and legal teams to establish standards for AI security, model governance, and ethical use of emerging technologies.

Your Role Responsibilities — Here’s What You’ll Do

AI Security & Governance

• Define and implement the organization’s AI security and governance framework, incorporating best practices from NIST AI RMF, ISO/IEC 23894, and relevant regional regulations such as the EU AI Act.
• Develop and enforce AI governance policies that align with internal risk appetite, ethical standards, and external regulatory obligations.
• Identify, assess, and mitigate AI-specific risks including model bias, adversarial attacks, data leakage, model inversion, and poisoning.
• Establish secure ML lifecycle practices including data sanitization, model hardening, explainability, and continuous monitoring for model drift and degradation.
• Collaborate with compliance and legal partners to maintain awareness of AI-related laws and standards (e.g., GDPR, Algorithmic Accountability Act).

Security Architecture & Risk Management

• Maintain and evolve threat models for AI and software systems, ensuring they remain current, comprehensive, and risk-informed.
• Lead reviews of software and model architectures to ensure compliance with established security and AI governance standards.
• Regularly assess and prioritize remediation of vulnerabilities in both internally developed and third-party AI components.
• Ensure security verification tools and AI audit mechanisms are effective, consistent, and automated where possible.

Governance, Monitoring, and Incident Response

• Design and oversee AI auditing and monitoring programs to ensure ethical and secure use of AI models post-deployment.
• Develop AI-specific incident response playbooks and lead investigations into security or ethics-related AI failures.
• Implement governance tooling and automation, leveraging ModelOps or compliance platforms (e.g., MLflow, OpenScale, Credo AI) to streamline audit logging and compliance checks.

Education, Culture, and Leadership

• Define and deliver education programs for engineers, data scientists, and testers on secure AI and software development practices.
• Foster a culture of ethical and responsible AI innovation, ensuring teams balance speed with security and compliance.
• Mentor and coach peers, providing feedback on best practices for AI governance and security-by-design.
• Act as a trusted advisor to leadership and cross-functional stakeholders on AI trends, risks, and emerging regulatory impacts.

Role Essentials — What You Bring

• Bachelor’s degree in Computer Science, Data Science, Information Security, or a related field.
• Minimum 8 years of progressive security architecture experience, with at least 3+ years in AI/ML system security, governance, or compliance.
• Strong understanding of secure development practices, cloud security (AWS/Azure/GCP), and compliance frameworks such as SOC 2, GDPR, and NIST.
• Hands-on experience with AI/ML pipelines, including data preparation, model deployment, and monitoring.
• Experience with SAST, DAST, SCA, and AI governance tools.
• Familiarity with AI ethics, fairness, and bias mitigation techniques.
• Demonstrated ability to translate technical AI risks into business language for non-technical stakeholders.

What We’d Like to See — Preferred Skills

• Experience implementing AI risk management frameworks (NIST AI RMF, ISO/IEC 23894, EU AI Act classifications).
• Scripting and automation skills (e.g., Python, PowerShell, or Java).
• Experience with policy development and cross-functional AI governance committees.
• Certifications such as CCSP, CISSP, or AI Governance/Responsible AI credentials….