🛠 Tech Stack

💼 About This Role

You'll design and operate the core MLOps platform infrastructure for production-grade AI and ML systems. You'll define how models and LLM-powered services are deployed, monitored, and managed at scale across cloud environments. This high-impact role combines deep cloud engineering, platform architecture, and MLOps expertise to shape developer experience and operational efficiency.

🎯 What You'll Do

• Build infrastructure as code using Terraform or AWS CDK
• Design CI/CD pipelines with GitHub Actions, GitLab CI, or CodePipeline
• Implement observability frameworks for ML/LLM systems
• Define environment isolation and model lifecycle management

📋 Requirements

• 7+ years in platform engineering, DevOps, MLOps, or cloud infrastructure
• Deep expertise in AWS production architecture and operations
• Strong experience with Terraform or AWS CDK
• Hands-on experience with Docker and orchestration (ECS, EKS, or Kubernetes)

✨ Nice to Have

• Experience managing ML/LLM workloads in production
• AWS certifications (Solutions Architect Associate or Professional)
• Kubernetes or CNCF certifications

🎁 Benefits & Perks

• 💰 Competitive salary $170,000–$190,000 OTE
• 🏥 Comprehensive medical, dental, and vision insurance
• 🏖️ Paid time off, holidays, parental and caregiver leave
• 🏠 Remote-friendly work environment
• 📚 Continuous learning support including certifications

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Initial phone screen· 30 min
2. 2Technical interview (cloud/MLOps)· 60 min
3. 3System design or platform architecture interview· 60 min