Staff Engineer (AI Security and DevSecOps )

Company Description 👋🏼We're Nagarro. We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at a scale — across all devices and digital mediums, and our people exist everywhere in the world (18500+ experts across 40 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in! Job Description 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 organization's AI security posture. Qualifications Bachelor’s or master’s degree in computer science, Information Technology, or a related field. Service Region: South Asia