Junior Security Engineer

About the Role

Our Fortune 500 client in New York, NY is seeking a motivated Junior Security Engineer to support the development and implementation of artificial intelligence and machine learning solutions that enhance cybersecurity operations. This is an excellent opportunity for an early-career technical professional interested in applying AI, machine learning, Python, and automation to real-world cybersecurity challenges, including threat detection, security log analysis, anomaly detection, and operational efficiency. Working alongside senior engineers and an Enterprise Architect, you will help develop, test, optimize, and support AI-powered security tools while gaining valuable experience with enterprise security technologies and modern engineering practices.

Job Location: New York, NY (Hybrid; 3 days onsite, 2 remote)

Pay Range: $50/hr (W2)

Interview Mode: 1st round via MS Teams, 2nd round onsite in New York, NY

Duration: 12 months+

Key Responsibilities

AI/ML Development & Security Analytics

• Assist in developing, testing, tuning, and monitoring AI/ML models supporting cybersecurity threat detection and anomaly identification.
• Analyze security logs, alerts, and telemetry to identify suspicious activity, unusual patterns, and potential security threats.
• Prepare, clean, organize, and label security datasets for machine learning model training and evaluation.
• Support model performance monitoring, testing, and continuous improvement.

Python Development & Security Automation

• Develop and maintain Python scripts to automate security-related tasks and workflows.
• Assist in integrating AI/ML capabilities into existing cybersecurity tools and security operations pipelines.
• Support automation initiatives that improve security monitoring, threat analysis, and operational efficiency.
• Troubleshoot scripts, data-processing workflows, and integrations with guidance from senior engineers.

Security Engineering & Integration

• Collaborate with cybersecurity, infrastructure, and engineering teams to support AI-driven security initiatives.
• Assist with the integration of AI-powered tools into existing security platforms and processes.
• Gain exposure to enterprise security monitoring, logging, threat detection, and incident-response workflows.
• Support the evaluation and improvement of AI-enabled cybersecurity solutions.

Documentation & Collaboration

• Maintain clear technical documentation covering AI models, datasets, scripts, integrations, and workflows.
• Participate in technical discussions, solution reviews, and troubleshooting activities.
• Work closely with senior engineers and architects to implement reliable, maintainable solutions.
• Continuously develop technical expertise in AI, machine learning, cybersecurity, and automation.

Requirements & Tech Stack

Qualifications

• Bachelor's degree in Computer Science, Cybersecurity, Data Science, Information Technology, or a related discipline, or equivalent practical experience.
• Working knowledge of Python programming, including scripting and basic automation.
• Foundational understanding of software development, data processing, or technical problem-solving.
• Strong interest in artificial intelligence, machine learning, cybersecurity, and security automation.
• Ability to analyze technical information, troubleshoot problems, and learn new technologies.
• Strong attention to detail, documentation skills, and analytical thinking.
• Excellent communication and collaboration skills.
• Willingness to learn from senior technical professionals and contribute to enterprise engineering initiatives.

Preferred Qualifications

• Familiarity with machine learning libraries such as scikit-learn, PyTorch, or TensorFlow.
• Basic understanding of cybersecurity concepts, including networking, logging, common threats, and security monitoring.
• Exposure to SIEM or SOAR platforms and security operations workflows.
• Familiarity with cloud environments such as Microsoft Azure, AWS, or Google Cloud Platform.
• Experience working with log data, telemetry, security alerts, or anomaly-detection techniques.
• Academic projects, internships, or personal projects involving Python, AI/ML, cybersecurity, or automation.
• Relevant certifications such as CompTIA Security+, Microsoft Azure Fundamentals (AZ-900), or comparable credentials.