Principal Engineer - AI​/ML

Role Overview

McAfee is a global leader in online protection. We are dedicated to making the digital world a safer place for everyone. We are seeking a highly experienced and hands‑on Technical Lead Software Engineer with deep expertise in cloud‑native architecture, agentic AI systems, strong background in full‑stack development, large‑scale internet services, and a proven track record of rapidly delivering AI/ML solutions into production.

This is a unique opportunity to lead critical projects, mentor talented engineers, and shape the future of McAfee's innovative security products through fast, iterative delivery focused on business outcomes. We highly value experience gained at FAANG or other leading Big Tech companies.

This is a Hybrid Position located in one of our hub offices of Frisco, TX, San Jose, CA, Newport Beach, CA, New York, NY, and in Toronto or Waterloo, Canada. We are only considering candidates within a commutable distance to these locations. You will be required to be onsite on an as-needed basis; when not working onsite, you will work from your home office.

• Lead the design, development, and deployment of scalable, resilient, and high-performance software solutions with a focus on agentic AI/ML capabilities.
• Provide hands‑on technical leadership throughout the entire software development lifecycle, from concept and design to testing, deployment, and operational support.
• Architect and build full‑stack applications and services that operate on an internet scale, ensuring high availability and low latency on modern cloud platforms (AWS, Azure, GCP).
• Drive the technical vision and strategy for AI/ML‑powered features and products, translating business requirements into robust technical designs with rapid iteration and incremental delivery.
• Mentor and guide a team of software engineers, fostering a culture of technical excellence, innovation, collaboration, speed, and AI‑augmented productivity.
• Collaborate closely with product managers, data scientists, researchers, and other engineering teams to deliver impactful solutions aligned with business goals.
• Leverage AI‑assisted development tools and practices to accelerate delivery (Git Hub Copilot, Claude Code, LLM‑powered workflows).
• Champion best practices in software engineering, including code quality, testing, CI/CD, and Dev Ops with a pragmatic, outcome‑driven approach.
• Stay current with emerging technologies and industry trends, particularly in AI/ML, agentic and LLM‑based systems, multi‑agent architectures, distributed systems, and cloud computing.
• Contribute to code reviews, design discussions, and architectural decisions with hands‑on involvement in implementation.
• Troubleshoot and resolve complex technical issues in production environments.

• 10+ years of professional software development experience, with a significant portion in a technical leadership role.
• Extensive hands‑on experience in designing, building, and operating large‑scale, distributed internet services.
• Proven experience in developing and deploying agentic AI systems and AI/ML models into production environments. This includes familiarity with the end‑to‑end MLOps lifecycle and modern LLM‑based architectures.
• Strong proficiency in multiple programming languages such as Python, Java, Go, Rust, C++ or similar.
• Deep understanding of full‑stack development, including front‑end technologies (e.g., JavaScript, Type Script, Dart, React, Flutter) and back‑end technologies (gRPC, protobuf).
• Experience with cloud platforms (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes) as a primary deployment model.
• Advanced Cloud & K8s Infrastructure:
  Deep expertise in Kubernetes (Helm, ArgoCD), advanced cloud networking (Ingress, Calico), Zero Trust Security (OPA), Service Mesh (Istio/Linkerd), and eBPF (Cilium) for high‑performance observability and traffic management.
• Solid understanding of database technologies (SQL and No
  
  SQL).
• Demonstrated use of AI productivity tools (Git Hub Copilot, Claude, ChatGPT, etc.) to accelerate software development.
• Bias for action: proven track record of fast, iterative, incremental delivery over analysis paralysis.
• Busines…