Staff Engineer (AI Security and DevSecOps )

Requirements

• Experience : 5.5 yrs 
• Strong experience in DevOps DevSecOps Cloud Infrastructure or AI/ML Security engineering.
• Strong experience in Machine Learning environments securing ML pipelines or LLM-powered applications.
• Hands-on experience building and securing unstructured data pipelines for AI/ML workloads.
• Proficiency in Python and Bash scripting for automation infrastructure management and security tooling.
• Experience with Infrastructure as Code (IaC) tools such as Terraform or Pulumi.
• Strong understanding of cloud platforms including AWS Azure or GCP and cloud security best practices.
• Experience implementing security controls across CI/CD pipelines including SAST DAST dependency scanning and secrets management.
• Solid understanding of OWASP security principles Zero Trust architecture and secrets management solutions such as HashiCorp Vault or AWS Secrets Manager.
• Experience implementing AI security controls including prompt injection mitigation input/output filtering abuse detection and secure LLM integrations.
• Knowledge of AI/ML security risks such as model inversion data poisoning prompt injection and adversarial attacks.
• Familiarity with data privacy regulations such as GDPR CCPA HIPAA and compliance frameworks including SOC 2 ISO 27001 or NIST AI RMF.
• Experience implementing data classification lineage tracking PII detection anonymization and retention policies.
• Knowledge of Kubernetes container security and cloud-native infrastructure hardening.
• Experience building observability monitoring and alerting solutions for AI systems infrastructure and security events.
• Familiarity with Azure DevOps pipeline strategy and CI/CD automation is an advantage.
• Exposure to AI/ML frameworks such as PyTorch LangChain vector databases or similar technologies is preferred.
• Professional certifications such as AWS Security Specialty CISSP CISM or Google Professional Cloud Security Engineer are desirable.
• Excellent analytical troubleshooting communication and stakeholder management skills.

Responsibilities

• Design implement and maintain security controls for AI/ML platforms and LLM-powered applications.
• Perform threat modeling for AI systems identifying and mitigating risks including prompt injection model inversion data poisoning and adversarial attacks.
• Implement guardrails input/output validation abuse detection and security controls for Generative AI applications.
• Conduct security assessments and reviews of third-party AI services APIs and model integrations.
• Monitor AI applications and infrastructure for security incidents anomalies and emerging threats and coordinate timely incident response.
• Design and secure data pipelines for structured and unstructured AI datasets while ensuring regulatory compliance.
• Implement data classification lineage tracking retention policies and governance frameworks for AI training and inference data.
• Develop and maintain PII detection anonymization and data protection mechanisms across AI datasets.
• Embed security throughout CI/CD pipelines using automated scanning dependency management secrets management and infrastructure validation.
• Provision and manage secure cloud infrastructure using Infrastructure as Code and cloud-native security best practices.
• Harden containerized environments and Kubernetes platforms to ensure secure AI application deployment.
• Build monitoring observability and alerting solutions for model performance drift detection infrastructure health and security events.
• Develop and maintain incident response playbooks for AI platforms cloud infrastructure and security-related events.
• Support security audits compliance assessments and documentation for regulatory and organizational standards.
• Collaborate with AI engineers DevOps teams data engineers and security stakeholders to deliver secure scalable and compliant AI solutions.
• Continuously evaluate emerging AI security threats industry standards and best practices to strengthen the organizations AI security posture.

Qualifications :

Bachelors or masters degree in computer science Information Technology or a related field.

Remote Work :

No

Employment Type :

Full-time