Security Delivery Lead

Project Role : Security Delivery Lead
Project Role Description : Leads the implementation and delivery of Security Services projects, leveraging our global delivery capability (method, tools, training, assets).
Must have skills : Product Security
Good to have skills : NA
Minimum 15 year(s) of experience is required
Educational Qualification : 15 years full time education

AI Security Architect – Enterprise AI Strategy, Scalable ML Platforms, and Secure AI Design We are looking for a seasoned and visionary AI Architect with 15+ years of experience in designing, securing, and leading scalable, responsible AI systems. This role blends AI solution architecture with security architecture and is ideal for professionals who bring together deep technical knowledge, strategic thinking, and a passion for trustworthy, ethical innovation. As an AI Architect, you will define the enterprise AI and security architecture, embed secure-by-design practices across AI platforms, and ensure alignment with privacy, compliance, and ethical standards across the entire ML lifecycle. Shape Key Responsibilities Strategic and Technical Responsibilities: Own the architectural vision for enterprise-wide AI and ML platforms, ensuring scalability, resilience, security, and regulatory compliance. Develop and maintain architectural blueprints for secure and responsible AI, covering areas such as bias mitigation, explainability, threat modeling, and data protection. Define and implement AI security architecture practices, including secure access to models, datasets, APIs, and ML pipelines. Collaborate with MLOps, engineering, DevSecOps, and cloud security teams to develop standardized, reusable, and secured AI infrastructure components. Ensure AI systems comply with global regulations and standards (e.g., GDPR, ISO 42001, NIST AI RMF, and ISO/IEC 27001). Evaluate and introduce tools and frameworks that support privacy-preserving AI, adversarial robustness, model security, and interpretability. Security & Governance Responsibilities: Lead efforts to design and enforce secure AI development workflows, from data ingestion to model deployment and monitoring. Partner with Security Architects and Risk teams to identify and mitigate AI-specific attack surfaces, including adversarial attacks and model poisoning. Conduct risk assessments and threat modeling for AI systems, including LLMs, generative models, and federated learning architectures. Collaborate with internal InfoSec, Privacy, and Legal stakeholders to align AI initiatives with enterprise cybersecurity strategies. Establish monitoring and incident response guidelines for AI workloads, including model drift, data leakage, and compliance alerts. Leadership & Organizational Responsibilities: Lead and mentor a multidisciplinary team of AI engineers, ML architects, and AI security specialists. Drive cross-functional initiatives with stakeholders in cloud, legal, compliance, and business domains to ensure holistic AI strategy implementation. Serve as a strategic advisor on AI and ML security topics across various business units and projects. Support the development and enforcement of enterprise-wide AI security and governance policies. Lead architecture review boards focused on AI and ensure consistent application of best practices across AI platforms. Shape Technical Experience 12+ years of experience in AI/ML solution architecture with 4+ years focused on AI security, governance, or compliance. Strong experience designing and deploying secure, large-scale ML systems in cloud and hybrid environments. Deep understanding of secure development practices, identity and access management (IAM) for ML workloads, model versioning, and auditability. Familiarity with: Cloud-native security tools (AWS IAM, KMS, GCP Workload Identity, Azure Key Vault) AI attack mitigation (e.g., adversarial training, input sanitization, model watermarking) Secure MLOps and CI/CD for AI Tools for model explainability (SHAP, LIME), monitoring (Prometheus, Grafana), and compliance tracking. Experience with data privacy, encryption techniques (at rest/in transit/in use), and secure federated learning is a plus. Shape Professional Attributes Proven leadership in AI security architecture and secure ML engineering practices. Exceptional stakeholder communication and ability to advocate for responsible AI across technical and executive teams. Strategic mindset with an ability to balance innovation with risk mitigation. Strong documentation, risk assessment, and audit reporting skills in security-centric environments. Shape Qualifications Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Information Security, or related field. Industry certifications preferred: Cloud AI (e.g., AWS Certified Machine Learning – Specialty, GCP ML Engineer) Security (e.g., CISSP, CCSP, Certified AI Security Professional, TOGAF) Proven success in building and securing AI platforms with strong focus on privacy, ethical AI, and regulatory compliance.15 years full time education

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