Profile- Al/ ML Security
Location- PAN INDIA
Exp-8+
Must Have
- 8+ years of experience in AI Security, Cybersecurity, Application Security, Cloud Security, or Model Assurance.
- Strong understanding of AI/ML systems, Generative AI, LLMs, RAG architectures, AI agents, and MLOps pipelines.
- Hands-on experience conducting security assessments across the AI/ML lifecycle, including data ingestion, training, deployment, inference, monitoring, and retirement.
- Experience performing AI threat modeling using frameworks such as MITRE ATLAS, OWASP Top 10 for LLMs, or NIST AI RMF.
- Experience securing and assessing LLM-based applications, RAG solutions, AI agents, and AI APIs.
- Hands-on experience with AI security testing, abuse-case analysis, and validation of AI security controls.
- Experience with AI model risk management and assurance frameworks.
- Experience securing AI/ML workloads deployed on GCP, or AWS.
- Solid knowledge of SSDLC, DevSecOps, CI/CD security, Infrastructure-as-Code, and cloud security best practices.
- Experience conducting application security reviews,



architecture assessments, vulnerability assessments, and penetration testing.
- Experience securing containers, Kubernetes platforms, APIs, and AI service endpoints.
- Knowledge of IAM, secrets management, encryption, and key management controls.
- Experience working within healthcare, medical device, life sciences, or other regulated environments.
- Familiarity with HIPAA, GDPR, FDA-regulated software environments, and security compliance requirements.
- Experience supporting audits, evidence collection, risk assessments, remediation tracking, and compliance reporting.
- Strong stakeholder management, communication, and technical documentation skills.

Good to Have
- Experience with AI Red Teaming and Adversarial Machine Learning testing.
- Hands-on experience with AI security tools such as Garak, PyRIT, Counterfit, Promptfoo, NVIDIA NeMo Guardrails, or similar.
- Experience assessing foundation mod

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