Senior Staff Engineer (AI Developer - AppSec)

As an Application Security Engineer at Nagarro, you will play a crucial role in designing, developing, and maintaining AI-powered application security solutions that seamlessly integrate into the software development lifecycle (SDLC). You will have the opportunity to work on innovative projects and collaborate with cross-functional teams to enhance security automation and developer experience. Key Responsibilities: - Design, develop, and maintain AI-powered application security solutions for seamless integration into SDLC. - Build intelligent SAST automation to contextualize findings, reduce false positives, and provide developer-friendly remediation guidance. - Develop secure code review assistants capable of identifying OWASP Top 10 and CWE Top 25 vulnerabilities during code reviews. - Implement machine learning models for Software Composition Analysis (SCA) to detect vulnerable dependencies, outdated libraries, and malicious packages. - Create DAST orchestration capabilities for automated attack surface discovery, vulnerability prioritization, and security testing. - Build Retrieval-Augmented Generation (RAG) pipelines for contextual security guidance leveraging internal knowledge bases and standards. - Develop agentic AI workflows to automate the vulnerability lifecycle from detection to remediation validation. - Integrate AI-powered security capabilities into CI/CD pipelines to enforce security gates and provide real-time feedback. - Develop developer-focused security tooling including IDE extensions, REST APIs, and microservices for contextual security recommendations. - Build aggregation platforms to consolidate findings from various security tools into a unified risk dashboard. - Develop intelligent secrets detection capabilities using pattern recognition and AI-based analysis. - Write unit tests, integration tests, and participate in peer code reviews to ensure high-quality, secure code. - Monitor AI model performance, track security metrics, and maintain automated retraining processes. - Develop CI/CD pipelines for AI model deployment, versioning, monitoring, and production release. - Prepare technical documentation including architecture designs, API specifications, and operational runbooks. Qualifications: - Bachelor's or master's degree in computer science, Information Technology, or a related field. - 7.5+ years of experience as an Application Security Engineer or similar role. - Strong expertise in Application Security principles, secure coding practices, and vulnerability assessment. - Hands-on experience with Application Security toolchains and programming skills in Python. - Experience with AI/ML libraries, REST APIs, and microservices development. - Knowledge of cloud platforms and containerization technologies. - Familiarity with security maturity frameworks and API security testing tools. - Excellent communication, collaboration, and problem-solving skills. Join Nagarro to be a part of a dynamic work culture and contribute to building secure and innovative digital products and experiences! As an Application Security Engineer at Nagarro, you will play a crucial role in designing, developing, and maintaining AI-powered application security solutions that seamlessly integrate into the software development lifecycle (SDLC). You will have the opportunity to work on innovative projects and collaborate with cross-functional teams to enhance security automation and developer experience. Key Responsibilities: - Design, develop, and maintain AI-powered application security solutions for seamless integration into SDLC. - Build intelligent SAST automation to contextualize findings, reduce false positives, and provide developer-friendly remediation guidance. - Develop secure code review assistants capable of identifying OWASP Top 10 and CWE Top 25 vulnerabilities during code reviews. - Implement machine learning models for Software Composition Analysis (SCA) to detect vulnerable dependencies, outdated libraries, and malicious packages. - Create DAST orchestration capabilities for automated attack surface discovery, vulnerability prioritization, and security testing. - Build Retrieval-Augmented Generation (RAG) pipelines for contextual security guidance leveraging internal knowledge bases and standards. - Develop agentic AI workflows to automate the vulnerability lifecycle from detection to remediation validation. - Integrate AI-powered security capabilities into CI/CD pipelines to enforce security gates and provide real-time feedback. - Develop developer-focused security tooling including IDE extensions, REST APIs, and microservices for contextual security recommendations. - Build aggregation platforms to consolidate findings from various security tools into a unified risk dashboard. - Develop intelligent secrets detection capabilities using pattern recognition and AI-based analysis. - Write unit tests, integration tests, and participate in peer code reviews to ensure high-quality, s