Principal AI Engineer
Description:
Principal AI Engineer – MLOps Cybersecurity AWS LLMs Kubernetes
My client, a leading innovator in AI-driven cybersecurity, is expanding their AI Center of Excellence and hiring a Principal AI Engineer – MLOps. This is a high-impact, hands-on leadership role focused on building scalable, production-grade ML infrastructure that powers advanced threat detection and response solutions.
This is an opportunity to work on cutting-edge AI/ML initiatives at the intersection of security, DevOps, and cloud-native engineering—solving real-world problems at scale.
Key Responsibilities
Define and lead MLOps strategy, best practices, and technical roadmap
Design, build, and optimize ML pipelines and deployment infrastructure (AWS, SageMaker, Terraform)
Develop, deploy, and monitor AI models in production environments
Collaborate closely with data scientists, ML researchers, and backend engineers
Build APIs and interfaces (Python, FastAPI, Flask, TypeScript) to power AI applications
Drive CI/CD, containerization, and orchestration using Docker and Kubernetes
Enable end-to-end automation, versioning, and governance of ML workflows
Support ongoing AI research and contribute to internal tools and platforms
Ideal Candidate Profile
Proven experience in MLOps, model deployment, and infrastructure engineering
Strong cloud experience, especially AWS (SageMaker, ECS, Lambda, etc.)
Skilled in Python and modern frameworks like FastAPI or Flask
Familiar with LLMs, distributed systems, and GPU-accelerated workloads
Hands-on with CI/CD, Docker, Kubernetes, and Terraform
Background in cybersecurity, data engineering, or DevSecOps is a plus
Excellent communication, problem-solving, and leadership skills
Why Apply?
Join a mission-driven company on the front lines of cybersecurity innovation
Work in a high-ownership role where AI models go from lab to live
Opportunity to contribute to published research, internal platforms, and strategic initiatives
Remote-flexible with high-impact, high-visibility projects