Senior Cybersecurity AI Engineer

Design, develop, and deploy AI agents that enhance information security and incident response capabilities. 

Build, maintain, and improve automated agents to handle routine, repetitive, and high‑volume security requests. 

Collaborate closely with security engineers and incident responders to translate operational requirements into effective AI‑driven automation. 

Continuously evaluate and refine automation to improve efficiency, reliability, and security outcomes. 

Work with large datasets and security data models to develop new automation capabilities and analytical features. 

Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, or a related field, or equivalent practical experience gained through relevant work, internships, bootcamps, or self‑directed learning. 

3+ years of experience in AI/ML, data engineering, or applied analytics in a production environment. 

Hands‑on experience building, deploying, and maintaining AI agents, including task orchestration, tool integration, and human‑in‑the‑loop controls for automation and decision support. 

Demonstrated implementation of AI/ML solutions in real‑world environments, showing practical application of models, workflows, or automations. 

Strong software development skills, with Python preferred (other languages acceptable). 

Experience supporting or automating tasks across data platforms, cloud infrastructure, APIs, or applications. 

Ability to translate technical AI/ML concepts into practical, usable workflows for teammates or broader organizational use. 

Strong understanding of workflow and process automation using AI/ML tools or frameworks such as TensorFlow, PyTorch, OpenAI, or similar platforms. 

Experience working with large‑scale security telemetry, including SIEM, EDR, identity, network, or cloud data sources. 

Experience applying DevOps and MLOps practices to AI systems, including CI/CD pipelines, model versioning, automated testing, and deployment strategies in cloud or hybrid environments. 

Proven experience designing, deploying, and operating AI‑powered solutions in production, supporting security operations or other mission‑critical operational workflows. 

Experience integrating AI/ML models and services into existing platforms via APIs, event‑driven architectures, or microservices, including retrofitting AI capabilities into established systems. 

Familiarity with observability and monitoring for AI systems, including performance metrics, drift detection, and operational health monitoring. 

Demonstrated ability to provide technical leadership and mentorship, including reviewing designs, guiding implementation decisions, and helping teammates adopt AI/ML tools, frameworks, and best practices.