DevSecOps Architect
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Job Description
DevSecOps Architect designing and building a self-healing DevSecOps ecosystem with AI automation for security. Focused on ensuring rapid deployment and uncompromising security standards for U.S. Government clients.
Responsibilities:
- Lead the evolution of the software delivery lifecycle by embedding security into every stage of the CI/CD pipeline
- 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
- 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)
- Develop AI-driven orchestration (SOAR) to automate the triage and remediation of security findings, reducing manual overhead for engineering teams
- Implement enterprise-wide governance using tools like Open Policy Agent (OPA) to enforce security compliance automatically across multi-cloud environments
- Conduct advanced threat modeling for cloud-native applications, specifically accounting for AI-specific attack vectors like model inversion or data poisoning
- Create self-service security tools and 'Golden Paths' that allow developers to deploy securely without friction, fostering a proactive security culture
- Achieve 90% automated security coverage across all production-bound code
- Utilize AI to reduce vulnerability remediation time by 40% within the first year
Requirements:
- A degree from an accredited College/University in the applicable field of services is required
- 10+ years of overall IT experience, with 5+ years dedicated to DevSecOps leadership in high-scale environments
- Proven track record of implementing AI/ML to solve operational or security challenges
- Expert-level experience with Kubernetes, Terraform/Pulumi, and cloud platforms (AWS, Azure, or GCP)
- Mastery of integrating SAST, DAST, SCA, and Secret Scanning into GitHub Actions, GitLab CI, or Jenkins
- Hands-on experience securing MLOps pipelines and implementing security for AI-integrated APIs
- Proficiency in Python, Go, or Bash for building custom security automation and AI-driven scripts
- Deep knowledge of eBPF, Prometheus, and AI-powered logging/monitoring tools (e.g., Dynatrace or Datadog)
- Strong ability to bridge the gap between 'Speed of DevOps' and 'Rigors of Security' while communicating clearly with executive leadership
- Excellent communication skills
Benefits:
- Must be able to pass a drug screening, criminal history, and credit checks
- Must be a US Citizen or have permanent residence status (Green Card)
- Must be able to obtain a Position of Public Trust Clearance
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