AI Agent Security
1 week ago
Role: AI Agent Security and Governance Engineer
Experience:
6–12 years
Location:
Hyderabad
Work Mode:
Hybrid (3 days/week in-office)
Domain:
Healthcare / Life Sciences
Join Time:
Immediate
Employment Type:
Full-Time/Contract
Role Summary:
We are seeking an
AI Agent Security & Governance Engineer
with strong cybersecurity expertise and practical understanding of AI/ML systems. In this role, you will secure enterprise AI agents, LLM applications, ML models, and data pipelines used across Healthcare and Life Sciences workflows. You will help define governance, enforce secure-by-design principles, safeguard sensitive data, and ensure responsible, compliant, and safe AI operations.
Key Responsibilities:
- AI/LLM Security Engineering
- Secure AI/ML pipelines, LLM APIs, RAG systems, vector databases, and agentic AI workflows.
- Implement controls against
prompt injection, adversarial ML attacks, data poisoning, model inversion, model theft
, and harmful agent actions. Embed security-by-design into AI development and deployment lifecycles.
Governance, Compliance & Risk Management
- Perform AI-focused
threat modeling
, bias risk assessment, and security posture evaluation. Develop processes for safe, explainable, auditable, and ethical AI usage Define AI governance controls for Healthcare/Life Sciences, ensuring compliance with
HIPAA, GDPR, SOC2
, and internal policies.Security Operations & Monitoring
- Monitor AI agents and ML models for drift, anomalies, misuse, hallucinations, and adversarial behavior.Investigate and resolve incidents involving AI security breaches or misbehavior.
- Build automated pipelines for red-teaming, adversarial testing, and model robustness validation.
- Collaboration & Cross-Functional Enablement
- Work closely with data scientists, ML engineers, DevSecOps, product owners, and clinical domain teams.
- Develop AI security documentation, runbooks, and governance playbooks.
Lead training sessions for engineering teams on AI/ML security best practices.
Required Skills & Experience
- 6–12 years
of experience across Cybersecurity, AI/ML Security, Application Security, or Cloud Security. - Cybersecurity expert
with proven hands-on experience implementing security protocols to safeguard AI systems, models, and data workflows. - Deep understanding of cyber security frameworks, methodologies, and industry standards
, including NIST, MITRE ATT&CK, OWASP, ISO27001. - Experience with
LangChain, LangGraph, Guardrails AI, Bedrock/Gemini/OpenAI
integrations. - Exposure to privacy technologies such as differential privacy, tokenization, and federated learning.
- Track record of staying current
with new AI threats, emerging vulnerabilities, and evolving security best practices. - Experience securing cloud environments (
AWS / GCP / Azure
) and containerized systems (Kubernetes, Docker). - Strong technical knowledge of LLM architecture, embeddings, RAG mechanisms, vector stores, and agentic AI frameworks.
- Familiarity with adversarial ML methods: prompt injection, model inversion, membership inference, data poisoning.
- Proficiency in Python or similar languages for automation and testing.
- Understanding of
Healthcare/Life Sciences security and compliance
(HIPAA, PHI, data sensitivity).
Apply Now
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