Principal MLOps Engineer / AI Infrastructure Architect

About
The company is a leader in the development of innovative secure communication products and solutions for governments and businesses. The Principal MLOps Engineer / AI Infrastructure Architect defines and leads the design, automation, and governance of the company’s AI infrastructure powering mission-critical, secure communications products. This role drives end-to-end MLOps strategy — from model governance and deployment automation to compliance enforcement — ensuring every AI capability adheres to zero-trust and sovereign-data principles. You will operate in an AI-augmented product development environment where infrastructure provisioning, model training, deployment, and monitoring are automated or AI-assisted.

Key Responsibilities

• Define the MLOps architecture and governance framework across products.
• Design secure, scalable AI platform blueprints covering data, training, serving, and monitoring layers.
• Lead architectural designs and reviews for AI pipelines.
• Develop and maintain AI agents for automation, such as automated test generation and log intelligence.
• Build continuous integration pipelines for models and code.
• Manage cloud infrastructure using Kubernetes and implement Infrastructure as Code.

Requirements

• BS in Computer Science, Computer Engineering, Mathematics, or a related field.
• 8+ years in DevOps, SRE, or platform engineering.
• 5+ years hands-on experience with ML/AI systems in production.
• Experience with container orchestration (Kubernetes).
• Strong Linux/Unix systems knowledge.

Key Skills

• MLOps & AI: LLM Integration, Model Serving
• Data Engineering: Pipelines, Processing
• DevOps & Infrastructure: Containers, Cloud Platforms
• Programming: Proficient in Python, SQL

Success Metrics

• Uptime: 99.9%+ availability for AI services.
• Deployment Frequency: Daily or on-demand deployments.
• Model Performance: Latency and accuracy tracking.