Key Responsibilities

Security Architecture & Strategy: Architect and maintain secure AI frameworks, focusing on Zero Trust, SASE, and micro-segmentation for AI/ML workloads.

AI/ML Security Engineering:

Design and deploy secure AI/ML pipelines, ensuring data integrity, confidentiality, and availability.

Implement safeguards for GenAI and LLM integrations (prompt injection protection, data leakage prevention, and output filtering).

Threat Detection & Incident Response:

Operationalize advanced threat detection using SIEM/SOAR platforms (e.g., Splunk, Sentinel, Cortex XSOAR).

Lead incident response for security breaches, ransomware, and APT events.

Perform threat hunting using IOC indicators and MITRE ATT&CK framework mapping.

Automation & Tooling: Leverage automation (Terraform, Python scripting) to enforce security guardrails and streamline vulnerability management and patch compliance.

Required Qualifications

Experience: 7+ years in Cybersecurity, with a strong focus on AI/ML security, Cloud Security (GCP/AWS/Azure), or SecOps.

Technical Proficiency:

SIEM/SOAR: Expert-level experience with platforms like Splunk, Microsoft Sentinel, IBM QRadar, or Cortex XSOAR.

Cloud Security: Deep understanding of IAM (Custom roles, OIDC/Federation), VPC Service Controls, and organization policy enforcement.

AI/ML Security: Familiarity with securing AI pipelines, automated prompt defense, and LLM orchestration frameworks

Vulnerability Management: Hands-on experience with scanners like Nessus, Qualys, Rapid7, and Burp Suite.

Compliance: Proven experience in audit readiness, including GRC implementations and managing security for cloud-native architectures.

Communication: Ability to articulate complex security risks and compensating controls to stakeholders and board-level management.

Preferred Skills (Boosters)

Experience with agentic AI workflows, autonomous systems, and red teaming/adversarial testing.

Knowledge of policy-as-code (OPA) and infrastructure-as-code (Terraform).