AI Engineer

• Design, develop, and operationalize full-lifecycle AI/ML operations (MLOps/LLMOps).
• Implement and deploy Retrieval-Augmented Generation (RAG) architectures in production.
• Build and maintain scalable AI orchestration frameworks and production-ready AI systems.
• Manage and optimize Kubernetes-based AI deployments, focusing on GPU inference optimization.
• Conduct core Python development for AI systems and integrate OpenAI-compatible APIs into mission solutions.
• Operationalize AI agents using advanced frameworks like LangGraph or Semantic Kernel.

Do you have experience in Production systems?, Do you have a Master's degree?, * Bachelor's degree in Computer Science, Engineering, or a related technical field.

• 5 or more years of experience in AI/ML production engineering, development, or related roles.
• Proven proficiency in Python development and experience with AI/ML libraries like TensorFlow or PyTorch.
• In-depth knowledge of MLOps/LLMOps principles and full machine learning lifecycle management.
• Experience with Kubernetes-based AI deployments and GPU optimization techniques., * Experience with LangGraph, Semantic Kernel, and agentic AI systems.
• Familiarity with Ray, NVIDIA GPU ecosystems, or Vector databases.
• Advanced degree (Master's or PhD) in a technical field.

Clearance Requirements:

• For onsite work, a TS/SCI clearance with polygraph will be required.

Physical Requirements:

• The person in this position must be able to remain in a stationary position 50% of the time.
• Frequently communicates with co-workers, management, and customers, which may involve delivering presentations.
• Constantly operates a computer and other office productivity machinery.