Key Responsibilities

• Develop AI-powered security automation integrated with CI/CD pipelines.
• Build ML models for anomaly detection, vulnerability analysis, and security scan findings.
• Develop LLM-based assistants for Terraform, ARM, and Helm configuration analysis and remediation.
• Implement RAG pipelines and AI agents for security scanning, policy compliance, and automated ticket creation.
• Build Python-based APIs and integrate security tools with SIEM/SOAR and ticketing platforms.
• Automate Docker, Kubernetes, container security, and policy enforcement workflows.
• Manage model monitoring, testing, CI/CD deployment, and MLOps activities.

Required Technical Skills

• Programming & ML: Python, scikit-learn, PyTorch, pandas, NumPy.
• AI/LLM: Azure OpenAI, OpenAI APIs, Prompt Engineering, RAG, LangChain.
• DevSecOps: SAST, SCA, Checkov, Terrascan, Trivy, secrets detection.
• CI/CD: Azure DevOps, GitHub Actions, Jenkins, GitLab CI.
• Cloud & Containers: Azure/AWS/GCP, Docker, Kubernetes, Terraform, ARM, Helm.
• Security & APIs: FastAPI/Flask, REST APIs, OPA/Rego, CSPM, Vault/Azure Key Vault.
• MLOps: Azure ML, MLflow, model monitoring, drift detection.

Required Experience

• 4–6 years in software engineering, including at least 1 year in AI/ML or security automation.
• Hands-on experience with DevSecOps tools, CI/CD security integration, Python development, and cloud security.

Preferred Certifications

CompTIA Security+, CEH, CKS, SC-200, AZ-900, AWS Security Specialty, or Google Professional Cloud Security Engineer.