Job Description & How to Apply Below
Location: Bengaluru
As a Principal Security Architect for AI & Data Security at FICO, you will define and drive the security architecture strategy for FICO's rapidly expanding AI ecosystem - from LLM-powered products and agentic AI systems to the data pipelines and analytical models that underpin our decisioning platform. FICO operates a growing fleet of internal AI agents, MCP servers, and ML training pipelines that process some of the world's most sensitive financial data.
You will influence product roadmaps, shape procurement decisions for AI security tooling, author security reference architectures, and serve as the authoritative voice on AI and data security risk at FICO. – Senior Director of Cyber Security
What You'll Contribute
Define and maintain FICO's AI security reference architectures and design patterns spanning LLM integrations, RAG architectures, agentic AI systems, MCP server deployments, and ML training pipelines.
Architect security controls across the AI model lifecycle - training data provenance, artifact signing, model registry governance, inference endpoint hardening, and runtime monitoring - ensuring FICO's analytical models are protected against data poisoning, model extraction, adversarial evasion, and prompt injection.
Drive architectural decisions for AI security platform selection and integration (AI-SPM, LLM firewalls, MLSecOps tooling).
Define the security strategy for FICO's AI consumption posture - centralized AI tool inventory, shadow AI detection, SaaS AI acceptable use enforcement, and developer workstation AI monitoring.
Support FICO's enterprise data security strategy encompassing data classification, DSPM, DLP, sensitive data discovery, and data lineage across cloud, SaaS, and on-premises environments.
Architect prompt-layer and AI-workflow data protection controls to prevent inadvertent leakage of sensitive data or proprietary model logic through AI tool interactions.
Lead security architecture for data governance within the Analytical Model Life Cycle, ensuring data quality, sanitization, and provenance tracking are embedded as security gates.
Serve as the trusted security advisor to product engineering, data science, and platform teams, translating complex AI and data security risks into business-consumable guidance for leadership and product management.
Participate in product planning cycles and architecture review boards, ensuring secure by design and privacy by design principles are embedded from the earliest stages of AI feature development and data systems.
Author and maintain AI-specific threat libraries aligned to MITRE ATLAS, OWASP LLM Top 10, and OWASP Agentic AI Top 10, and lead AI-specific threat modeling for FICO products.
Set the direction for AI security standards, policies, and governance frameworks aligned to EU AI Act, NIST AI RMF, ISO 42001, and applicable regulations, in coordination with GRC and legal teams.
Collaborate with Cyber Security Operations, Incident Response, and Security Engineering teams to ensure AI-specific detection use cases, logging standards, and response playbooks are operationally viable.
What We're Seeking
A collaborative leader who raises the bar for the team and brings clarity in ambiguous, fast-moving situations.
Deep architectural understanding of AI/ML security risks across the full lifecycle: training data integrity, model supply chain, inference security, prompt injection/jail breaking, model extraction, adversarial attacks, and AI agent governance.
Experience architecting security for LLM-based applications, RAG systems, agentic AI frameworks, and multi-model orchestration (e.g., MCP, tool-use patterns, AI gateways).
A hands-on builder's mindset - strong software engineering skills in Python and/or Java, with a bias toward writing code, building tooling, and automating security controls rather than producing paper artifacts.
Strong architectural experience with enterprise data security: DSPM, DLP, data classification, sensitive data discovery, encryption, key management, and data access governance.
Extensive architectural understanding of cloud security, Kubernetes, cloud-native computing, and microservices.
Experience at an…
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