INSenior AssociateAI Security SMEDigital IntegrationAdvisoryKolkata

We are looking for a Senior AI Security Subject Matter Expert (SME) to provide technical AI tooling reviews and hands-on engineering support for our AI security program. This is a role for a builder-defendersomeone who can critically evaluate emerging AI technologies architect secure integration patterns and execute tactical security initiatives.

The ideal candidate acts as a bridge between high-level security strategy and ground-level implementation capable of performing deep-dive technical assessments one day and advising business stakeholders on safe AI adoption the next.

In priority order the SME will focus on three primary areas:

1. Review security architecture and controls for AI tools on an ad hoc request basis from the business.

2. Identify high-priority AI needs across our security domains and business to inform AI intake and adoption.

3. Assist teams with building AI into their processes consulting on options architecture and implementation where needed.

Responsibilities

Technical Leadership & Delivery: Drive the technical implementation of security controls moving beyond theory to practical application. execute on configuration integration and tuning of security platforms.

Security Architecture & Design: Review and design secure patterns for AI system integration ensuring alignment with enterprise security standards. Provide expert guidance on build vs. buy decisions and secure deployment models.

Technology Evaluation & PoC Execution: Conduct rigorous technical assessments of emerging security tools and AI platforms. Define test cases execute hands-on validation and provide data-driven recommendations.

Threat Modeling & Risk Assessment: Perform threat modeling for AI use cases identifying risks related to prompt injection data leakage and model manipulation (OWASP Top 10 for LLM).

Advisory & Governance: Serve as the primary technical advisor for business units proposing new AI use cases. Triage requests to determine appropriate security pathways (e.g. enterprise platform vs. custom development).

Qualifications

Required Experience

Security Engineering: 5 years of experience in Application Security Cloud Security (AWS/Azure/GCP) or DevSecOps.

AI/ML Security: Practical experience with Generative AI architectures (LLMs RAG) and associated security risks. Familiarity with AI safety frameworks (NIST AI RMF OWASP LLM).

Technical Assessment: Proven track record of evaluating third-party vendors and technologies against strict security requirements.

Technical Skills

Scripting & Automation: Proficiency in Python or similar languages to write scripts for API testing automation or light prototyping.

Architecture: Strong understanding of API security OAuth/OIDC containerization (Docker/Kubernetes) and cloud-native services.

Tooling: Experience with Security Posture Management (CSPM/ASPM) tools and vulnerability scanners.

Core Competencies

Analytical Thinking: Ability to dissect complex technical problems and identify subtle security flaws.

Communication: Strong ability to explain complex AI security risks to non-technical stakeholders and business leaders.

Stakeholder Management: Ability to build trust with engineering product data science and governance partners; influence decisions without direct authority.

Curiosity & Depth: Proactive learner who can quickly dive deep into new AI technologies architectures and failure modes.

Adaptability: Comfort working in a rapidly evolving technology landscape with high ambiguity.

Preferred (Bonus)

Experience with specific AI security tooling and vendors