Description

You will lead the design and enforcement of security architectures across AI and machine learning platforms.

Responsibilities

• Design end-to-end security for AI/ML systems, including training pipelines, data ingestion, inference APIs, and agentic AI orchestration.
• Conduct threat modeling and risk assessments for AI applications, addressing adversarial attacks, prompt injection, and data leakage.
• Establish and enforce AI-specific security policies, including audit trails, data access controls, and responsible AI guidelines.
• Guide engineering teams on secure development practices for AI workloads running on cloud-native infrastructure.
• Implement security automation tools within CI/CD pipelines and define AI-specific observability strategies.

Required Skills

• 12+ years in software engineering, with 8+ years in software security architecture.
• 2+ years focused specifically on AI/ML platforms or services.
• Deep understanding of cloud security principles (IAM, encryption, secrets management).
• Hands-on experience securing LLM applications, API endpoints, and prompt engineering.
• Strong coding and architecture skills in Python, Typescript, or Java.
• Experience with secure CI/CD practices using GitHub Actions or Azure DevOps.
• Familiarity with infrastructure-as-code using Terraform or Pulumi, and Kubernetes security.
• Experience with ML pipeline security concepts (e.g., model lifecycle management).
• Knowledge of securing systems on Azure, AWS, and GCP.

Key Skills

Education

Any Graduate