OT Network & Security Architect

To design, implement, and govern secure, scalable, and resilient OT network and security architectures across AECI’s industrial environments. This includes integration of Data AI, IT and OT systems, ensuring cybersecurity compliance, and supporting digital transformation initiatives in mining, chemicals, agriculture, and water treatment operations.

Roles and Responsibilities

• Lead the architecture and design of Data AI and OT networks including SCADA, MES, PLC, and IIoT systems.
• Define and enforce network segmentation, secure zones, and DMZs between IT and OT environments.
• Implement cybersecurity controls aligned with NIST, IEC 62443, and POPIA.
  
• Collaborate with engineering, cybersecurity, and IT teams to align architecture with business needs.
• Evaluate and select vendor technologies for firewalls, IDS/IPS, SIEM, PAM, and end-point protection
• Provide input to Risk and Compliance Assessments reports
• Develop and maintain architecture blueprints, standards, and governance models.
• Conduct risk assessments, vulnerability scans, and penetration testing in OT environments.
• Ensure compliance with industry regulations and internal security policies.
• Support incident response and forensic investigations in OT networks.
• Ensure seamless data movement across platforms to enhance accessibility.
• Integrating disparate data sources to create a unified and consistent data environment.
• Build scalable architectures that support AI models and machine learning applications.
• Implementing policies to ensure data integrity, compliance, and protection.
• Leverage integrated data insights to improve business intelligence and strategic planning

Qualifications and Experience

• Must hold a Bachelor’s Degree in Computer Science, Information Technology, Engineering or any related field.
  
• Advantageous: 
  • Certifications: TOGAF, CISSP, CCNP Security, ISA/IEC 62443
  • AWS Certified Machine Learning – Specialty – Focuses on AI and ML solutions in AWS.
  • Microsoft Certified: Azure AI Engineer Associate – Covers AI solutions in Azure.
  • Google Professional Machine Learning Engineer – Specializes in AI and ML on Google Cloud.
• Extensive (10+ years) experience in network architecture, with at least 3 years in OT environments, data management, cloud computing, and AI-driven solutions
• Experience with SD-WAN, SASE, NGFW, VPN, and segmentation technologies
• Hands-on experience with tools like Fortinet, Palo Alto, Cisco, CyberArk, Splunk, and Azure/AWS.

Technical Skills and Knowledge

• Data Integration – Expertise in ETL processes, APIs, and data pipelines.
• AI & Machine Learning – Strong understanding of deep learning, NLP, and predictive analytics.
• Cloud Platforms – Experience with AWS, Azure, or Google Cloud.
• Big Data Technologies – Proficiency in Hadoop, Spark, NoSQL databases, and data lakes.
• Strong understanding of SCADA, DCS, PLC, and industrial protocols (Modbus, OPC-UA, etc.).
• Familiarity with cybersecurity frameworks (NIST, IEC 62443, ISO 27001).
• Knowledge of IT/OT convergence and hybrid cloud architectures.
• Networking – Strong knowledge of Software defined networks, TCP/IP, VPNs, firewalls, and load balancing
• Security & Compliance – Experience with security frameworks, encryption, and regulatory standards.
• DevOps & Automation – Familiarity with CI/CD pipelines, Kubernetes, Docker, and Terraform
• Solution Design – Experience in designing scalable, secure cloud solutions.
•  Cost Optimization – Implementing cost-effective cloud infrastructure strategies

Key Competencies

• Problem Solving – Ability to troubleshoot complex network and cloud issues.
• Communication – Clear articulation of technical solutions to stakeholders.
• Leadership – Guiding teams in cloud adoption and network optimization.
• Strategic Thinking – Aligning cloud solutions with business objectives
• Stakeholder Collaboration – Working with business leaders to align cloud solutions with company goals.

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