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Job Description
Structured overview of role & requirementsAbout This Role
Own identification and remediation of AI-specific vulnerabilities across multi-cloud LLM platforms, using automation and secure AI guardrails.
Develop and maintain automated tools for AI asset discovery, topology mapping, risk classification, vulnerability detection, and self-healing remediation pipelines with Python and GoLang.
Ensure all AI workloads comply automatically with OWASP Top 10 for LLMs, NIST AI RMF, and emerging regulatory frameworks, integrating security controls into CI/CD and conducting adversarial testing.
Minimum Requirements
3 to 5 years of experience specifically in AI security development or related AI security tooling.
Strong expertise in Python (5+ years) for automation and AI security tooling; hands-on experience in GoLang for scalable security tools development.
Proven experience with multiple cloud AI platforms: Azure OpenAI SDK, AWS Bedrock SDK, Anthropic Claude SDK, Google Vertex AI SDK, and OpenAI SDK.
Work Experience Required: 3 to 5 years in AI security development; Notice Period: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced in cross-cloud AI security platform development with deep practical knowledge of securing AI/LLM-based applications and retrieval-augmented generation (RAG) systems.
Operates effectively in highly technical roles requiring automation scripting, security toolchain development, and compliance alignment with frameworks like NIST AI RMF and OWASP for LLMs.
Ability to integrate security practices deeply into DevOps/CI/CD pipelines and conduct adversarial and red-teaming tests on AI applications at scale across multi-cloud environments.