Principal AI/ML Engineer (Cybersecurity & AIOps)

As a Principal AI Engineer, you will serve as a strategic technical leader responsible for the vision, architecture, and execution of AI/ML initiatives across the enterprise. You will bridge the gap between complex data science and mission-critical security operations, designing intelligent systems that detect risks, optimize network performance, and automate threat response. This is a high-impact leadership role requiring a blend of hands-on engineering excellence, architectural oversight, and the ability to influence cross-functional stakeholders.

Responsibilities:

• Lead the design, development, and deployment of advanced AI/ML solutions focused on cybersecurity, network analytics, and enterprise risk detection.
• Build and operationalize machine learning models, including anomaly detection, predictive analytics, and classification systems for security and network use cases.
• Drive the implementation of Generative AI and Agentic AI solutions to enhance automation, threat intelligence, and decision-making workflows.
• Collaborate with cybersecurity, network engineering, and IAM teams to identify opportunities for AI-driven optimization and risk mitigation.
• Architect end-to-end ML pipelines, ensuring scalability, reliability, and integration with enterprise systems.
• Work hands-on with data,ingestion, preprocessing, feature engineering, and model tuning,to deliver production-grade solutions.
• Translate complex technical outcomes into business insights using dashboards and visualizations (e.g., Power BI) for stakeholders and leadership.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field
• 12+ years of experience in software engineering, data science, or AI/ML solution delivery
• Proven experience in designing, building, and deploying scalable AI/ML solutions in enterprise environments
• Strong programming skills in Python and proficiency in SQL
• Hands-on experience in machine learning model development, evaluation, and deployment
• Working knowledge of cybersecurity concepts, network architectures, and Identity & Access Management (IAM)
• Experience with data visualization tools such as Power BI (or equivalent)
• Familiarity with Agile tools such as JIRA
• Exposure to cloud platforms (Azure, AWS, or GCP) and MLOps practices
• Strong problem-solving, stakeholder management, and communication skills