Job Title: Architect Premium III Sr. Security Architect (CISSP & Azure Cloud Implementation) (W2)
Location: Washington DC 20433
Duration: 12 Months Long Term W2 Contract
Position Summary:
We are seeking a highly experienced Security Architect with strong hands-on expertise in Azure Cloud Security AI/ML technologies and DevSecOps practices. This role will lead enterprise-level security strategy and architecture initiatives with a focus on cloud-native applications infrastructure as code(IaC) and AI/ML integrations.
Key Responsibilities:
- Design and implement enterprise security architecture across cloud (Azure preferred) AI/ML workloads and application layers.
- Conduct security reviews and threat modeling for new and existing solutions.
- Integrate DevSecOps practices and Infrastructure-as-Code (IaC) frameworks into application and infrastructure pipelines.
- Work collaboratively with cross-functional teams including infrastructure data science DevOps and compliance.
- Drive secure implementation of APIs Gen AI and machine learning solutions.
Top Required Skills:
- Development background with a transition into security-focused architecture roles.
- Proficiency with IaC tools such as Terraform CloudFormation ARM Templates and Ansible.
- Expertise in API Security and modern identity protocols.
- Experience with Azure Cloud Services (PaaS and IaaS).
- Familiarity with Office 365 Security and integration.
- Solid understanding of AI/ML technologies and Generative AI.
- The ideal candidate will have a background in development and has upskilled to become a security architect focusing on cybersecurity rather than compliance.
- Strong experience in API security is required ensuring the protection and integrity of APIs through robust security practices and protocols.
Preferred:
- Microsoft Certified Cloud Solution Architect
- Certified Information Systems Security Professional (CISSP) - Must Have
- Additional cloud security certifications are a plus.
Preferred Experience:
- Experience in Agile/Scrum and DevSecOps environments.
- Prior work in organizations with significant AI/ML initiatives.
- Knowledge of security within containerized environments (e.g. Kubernetes Docker).