AI Modeler (SoD Resolution)

- **Cloud Security Operations:**
- Implement and monitor OCI security measures (network security, encryption, secrets management).
- Oversee compliance, governance, and incident response processes.
- Utilize tools like Visual Builder Studio and CI/CD pipelines for secure deployments.

- **Risk & Compliance:**
- Conduct Oracle Cloud Security assessments and design implementations.
- Ensure adherence to ERP security best practices and regulatory requirements.
- Collaborate with audit teams to maintain compliance posture.

- **Application Security:**
- Manage Oracle application security consoles.
- Create custom security profiles and data roles.
- Support secure integration of business processes with Oracle Cloud applications.

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## Required Skills & Qualifications
- **Experience:** 3-8 years in Oracle Cloud Security or related IT security roles.
- **Technical Knowledge:**
- Strong understanding of OCI security features and best practices.
- Familiarity with encryption, key management (OCI Vault), and secure networking.
- Hands-on experience with Visual Builder Studio, CI/CD, and cloud monitoring tools.
- **Business Acumen:** Ability to align security controls with ERP processes and organizational risk management strategies.
- **Soft Skills:** Analytical thinking, problem-solving, and clear communication with both technical and non-technical stakeholders.

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## Typical Deliverables
- Secure cloud architecture designs.
- Custom IAM roles and policies.
- Compliance and audit reports.
- Incident response playbooks.
- Continuous monitoring dashboards for cloud security posture.

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## Challenges & Risks
- **Evolving Threat Landscape:** Engineers must stay updated on new vulnerabilities in cloud environments.
- **Complex Role Customization:** Misconfigured roles can lead to privilege escalation risks.
- **Compliance Pressure:** Ensuring adherence to global standards (GDPR, ISO, SOC2) requires constant vigilance.
- **Integration Issues:** Balancing security with usability in ERP workflows can be difficult.

Graduate/Engg.

Key Responsibilities

• Model Development - Build and implement machine learning and deep learning models for prediction, classification, and optimization.
• Data Preparation - Collect, clean, transform, and preprocess structured and unstructured datasets for model training and evaluation.
• Algorithm Research - Explore and apply advanced AI techniques such as reinforcement learning, NLP, and computer vision where relevant.
• Model Evaluation - Validate, test, and tune models to ensure accuracy, robustness, fairness, and compliance.
• Deployment - Integrate AI models into production environments using APIs, cloud platforms, or enterprise applications.
• Monitoring - Continuously track model performance, detect drift, and implement updates or retraining cycles.
• CrossFunctional Collaboration - Partner with GRC, security, and engineering teams to identify AI use cases and translate business needs into technical solutions.
• Documentation - Produce technical documentation, model guidelines, and compliance artifacts.
• Ethics & Security - Ensure responsible AI development, data privacy, and adherence to regulatory and organizational standards.