- 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.

- Conduct hands-on security assessments across the AI/ML lifecycle, including data ingestion, training, deployment, inference, monitoring, and retirement.

- Perform 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.

- Conduct hands-on 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.

- Robust knowledge of SSDLC, DevSecOps, CI/CD security, Infrastructure-as-Code, and cloud security best practices.

- Conduct 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.

- Support 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.

- Have hands-on experience with AI security tools such as Garak, PyRIT, Counterfit, Promptfoo, NVIDIA NeMo Guardrails, or similar.

- Assess foundation models, fine-tuned models, multimodal AI systems, and healthcare AI solutions.

- Implement AI guardrails, content moderation controls, safety mechanisms, policy enforcement, and human-in-the-loop workflows.

- Experience securing agentic AI systems, autonomous workflows, MCP integrations, and tool-calling architectures.

- Familiarity with AI observability, model monitoring, prompt monitoring, drift detection, and AI security telemetry.

- Knowledge of the EU AI Act, FDA AI/ML SaMD guidance, Good Machine Learning Practice (GMLP), NIST AI RMF, and ISO 42001.

- Support AI governance, assurance, compliance, and risk management programs.

- Understand Responsible AI, Explainable AI (XAI), bias assessment, fairness testing, and transparency requirements.

- CISSP, CCSP, CEH, GIAC, or equivalent security certifications.

- AWS, Azure, or Google Cloud security certifications.

- AI Security, AI Governance, or Machine Learning Security certifications

📌 Security Engineer (Bengaluru)
🏢 Etenico Technologies
📍 Bengaluru