Senior DevSecOps Engineer/Architect

As a Senior DevSecOps Architect, you will lead the evolution of our software delivery lifecycle by embedding security into every stage of the CI/CD pipeline. This role is specifically focused on leveraging Artificial Intelligence to automate threat detection, optimize code reviews, and secure AI-native applications. You will be responsible for building a robust, self-healing DevSecOps ecosystem that balances rapid deployment with uncompromising security standards.

Key Responsibilities

• AI-Enhanced Pipeline Security: Architect and maintain automated CI/CD pipelines that utilize AI/ML models for static and dynamic analysis (SAST/DAST) to identify complex vulnerabilities that traditional rule-based tools miss.
• Securing AI Workflows: Design security frameworks for the end-to-end AI lifecycle, including securing data ingestion, protecting model weights, and implementing "Guardrail" architectures for Large Language Models (LLMs).
• Intelligent Automation: Develop AI-driven orchestration (SOAR) to automate the triage and remediation of security findings, reducing manual overhead for engineering teams.
• Policy as Code (PaC): Implement enterprise-wide governance using tools like Open Policy Agent (OPA) to enforce security compliance automatically across multi-cloud environments.
• Threat Modeling & Red Teaming: Conduct advanced threat modeling for cloud-native applications, specifically accounting for AI-specific attack vectors like model inversion or data poisoning.
• Developer Empowerment: Create self-service security tools and "Golden Paths" that allow developers to deploy securely without friction, fostering a proactive security culture.

Technical Qualifications

Preferred Experience

• Experience: 10+ years in IT, with at least 5 years dedicated to DevSecOps leadership in high-scale environments.
• AI Expertise: Proven track record of implementing AI/ML to solve operational or security challenges.
• Education: Advanced degree in Computer Science, Cybersecurity, or a related engineering field.
• Soft Skills: Strong ability to bridge the gap between "Speed of DevOps" and "Rigors of Security" while communicating clearly with executive leadership.

Core Objectives

• Shift Left: Achieve 90% automated security coverage across all production-bound code.
• Mean Time to Remediate (MTTR): Utilize AI to reduce vulnerability remediation time by 40% within the first year.
• Innovation: Stay at the forefront of the "AI for Security" and "Security for AI" movements