🛠 Tech Stack

💼 About This Role

You'll operationalize advanced AI and agentic AI systems within production mission environments. Your work will center on implementing a modern Hub-and-Spoke architecture to accelerate enterprise AI adoption. You'll integrate AI solutions with DevSecOps and cybersecurity for scalable, secure deployments.

🎯 What You'll Do

• Design and operationalize AI and agentic AI systems for production
• Implement LLMOps and MLOps workflows for AI production engineering
• Architect and deploy Retrieval-Augmented Generation (RAG) solutions
• Manage Kubernetes-based AI deployments with OpenAI-compatible APIs

📋 Requirements

• AI/ML production engineering or LLMOps/MLOps experience
• Experience deploying Retrieval-Augmented Generation (RAG) architectures
• Kubernetes-based AI deployments and Python development
• GPU inference optimization within NVIDIA GPU ecosystems

✨ Nice to Have

• Exposure to LangGraph, Semantic Kernel, vLLM, Ollama, Ray
• Experience with vector databases
• Integrating observability and cybersecurity into AI platforms

🎁 Benefits & Perks

• 🏖️ Unlimited PTO
• 📚 Industry training and certifications
• 💻 Hands-on experience
• 🏥 Comprehensive benefits

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min

🚩 Heads Up

• Active TS/SCI clearance required, limiting candidate pool