Drive the architecture, design, and implementation of cloud security solutions utilizing AI/GenAI technologies to address emerging security threats.
Develop and deploy custom security tooling in languages such as Python or Go for data masking, model integrity verification, and adversarial testing.
Build security guardrails across the entire AI/ML lifecycle, from secure data ingestion and training to production monitoring and retrieval-augmented generation pipelines.
Map and mitigate risks specific to generative and agentic AI, including prompt injection, model inversion, and output tampering.
Gather and analyze performance and compliance metrics to ensure adherence to security standards and policies.
What's Needed?
3–5+ years of experience in application security, cloud security (AWS, GCP, or Azure), or platform engineering.
Proficiency in designing and deploying cloud integration solutions using AI Agents and AI Models.
Familiarity with AI frameworks such as TensorFlow or PyTorch and understanding of adversarial manipulation of intelligent systems.
In-depth experience with Terraform, scripting languages like Bash or Python, and container platforms such as Kubernetes or OpenShift is highly desirable.
Strong understanding of DNS, PKI, encryption, key management, and cloud security principles within regulated environments