Principal Ai/Ml Engineer (Cybersecurity & Aiops)

The Principal Engineer- AIOps role at EPEO requires 12+ years of experience in AI/ML and software engineering with strong skills in Python, SQL, and cloud platforms. This position focuses on designing and deploying advanced AI/ML solutions for Security (Cyber & Identity Management) , network analytics, enterprise risk detection and thus strengthening the security posture across Ford skill teams such as ET , Credit , Ford Pro ,AV , EV , Industrial systems ,Ford PDO's etc.

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.

The Principal Engineer- AIOps role at EPEO requires 10+ years of experience in AI/ML and software engineering with strong skills in Python, SQL, and cloud platforms. This position focuses on designing and deploying advanced AI/ML solutions for Security (Cyber & Identity Management) , network analytics, enterprise risk detection and thus strengthening the security posture across Ford skill teams such as ET , Credit , Ford Pro ,AV , EV , Industrial systems ,Ford PDO's etc.

• 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.

• 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.