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# AI Architect, MLOps / DevOps / Cloud Engineering

- **Company:** GE Vernova
- **Location:** United States
- **Experience:** Expert
- **Salary:** $113,200
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Airflow, Machine Learning, Prometheus, Enterprise Data Management, Grafana, Multi-Agent Systems, IT Architecture, Agentic-AI, AI Platforms, Kubernetes, Information Technology, CrewAI, Nintex, Machine Learning Operations, Terraform, Engineering Base
- **Published:** November 13, 2026
- **Apply:** https://jobs.military.com/career/396473/senior-ai-mlops-devops-cloud-architect-south-carolina-sc-greenville

## About the Role

* Bachelor's degree in Engineering, Computer Science, Applied Mathematics, Data Science, or a related technical field; advanced degree strongly preferred. \n
 * Significant hands-on experience designing, building, and deploying AI or machine learning solutions in complex technical environments, with demonstrated progression to enterprise-level architecture responsibilities. \n
 * Experience defining technical standards, reference architectures, and design practices across a portfolio of AI solutions. \n
 * Familiarity with AI/ML systems in production (e.g., Kubernetes, MLflow or similar registries, Terraform, Airflow/Kubeflow, Prometheus/Grafana) and enterprise data platforms. \n, * Ability to partner effectively with engineering leaders, Digital/IT teams, platform owners, and governance stakeholders. \n
 * Strong communication skills, with the ability to explain complex technical concepts to non-technical audiences and translate architecture standards into practical guidance. \n
 * Experience with ARC Foundry, AMP, or GE Vernova enterprise AI platforms and integration patterns. \n
 * Familiarity with agentic AI frameworks (e.g., n8n, LangGraph, CrewAI) and experience designing multi-agent workflow architectures for engineering applications. \n
 * Experience mentoring and developing AI engineering talent across distributed teams or matrixed organizations. \n
 * Comfortable with Lean and engineering standard work concepts, with the ability to apply AI architecture thinking to process improvement and waste elimination. \n
 * Strong ownership mindset, equally comfortable driving technical strategy at the enterprise level and reviewing detailed subsystem-level design decisions. \n
 * Technical escalations are resolved promptly, with documented architecture decisions and rationale available for future reference. \n