AI Security Architect - Senior Manager

Role & responsibilities

Conducted Threat Modeling for 23 cendyn products and reduced the attack surface up to 80% ? Onboarded Cycode tool to scan Cendyn products and worked with platform team to integrate in CI/CD build pipeline ? Performed AppSec tool stack gap assessment for the application security build pipeline. ? Developed and introduced Risk Management and Risk Assessment policies and template to calculate the impacted assets and severity level. ? Conducted POCs on secret detection and software composition analysis for Cendyn CRS product ? Developed and rolled out the SSDLC policy and processes across the Cendyn development environment. ? Established the Security Champions Community of Practice to strengthen security ownership across teams. ? Performed product security reviews for the Cendyn CRS product, including threat modeling, secret detection, software composition analysis, static analysis (SonarQube), API security, dynamic testing (BurpSuite/Rapid7 AppSec), and penetration testing. ? Defined and reported KPI metrics for the CRS product, presenting results to management during QBR meetings. ? Developed the policies for usage of AI/ML in Cendyn product development and Secure LLM based product development to align with OWASP and AI Compliance and Governance. ? Participating in AI Compliance meetings(India, China, Europe and US) ? First time in Cendyn History Instituted SECURITY CHAMPIONS PROGRAM - 27, trained for security best practice and ensure security deliverables. ? Participate in release meetings to give signoff for security reports. AI Security Ownership ? Written Secure AIDCL policies to adopt AI Security best practices towards Shift – Left to Left” approach starting from Secure Prompts to Bedrock and Enterperise LLM Deployments (L-11 Spec Driven Development) ? Instituted AI Security Program at Cendyn to ensure all security controls and guardrails are in place including AI Governance ? Performing Threat modeling for AI Model Gateway, MCP Registry, Wayfinder Framework and also to ensure AI Agent pipeline security, Multi-tenant cloud infrastructure, etc. ? Reviewing AI Generated coding patterns – best practices. ? Working on Hardening AI generated application environment. ? LLM usage experience – Claude, Copilot, ChatGPT, KIRO ? Tools: Cycode(SAST/SCA/Secret Detection/Code leakage/CI/C Misconfiguration), Rapid7 AppSec, Pentest vendors ? Attended AI Red Teaming training conducted by Nullcon, Goa. ? Deployed Cycode’s AIDLC guardrails to address OWASP GenAI/LLM/Agent Top 10 security vulnerabilities. ? Policies: AI Acceptable use, AI Governance, AI Security program ? Claude Projects: (Tools’ cost saving – $40K-$80K USD) • Build Threat Modeling Agent / DPIA agent • Vulnerability Dashboard (Risk Register) • DPDPA internal tool ? AI Risk Assessment: • Noma Fuse – AI Observability Security & Privacy Threat Modeling • Agent OS – Security & Privacy Threat Modeling • Cycode AI Observability – Input/Output filer in AISecOps pipeline integration

Preferred candidate profile

Immediate joiners

Excellent Communication

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