We are looking for a highly skilled Enterprise Cloud and AI Ops Architect to join our team in Denver. This role is pivotal in designing and implementing AI-driven operational frameworks and cloud-native architectures that enable autonomous networks and intelligent automation. The ideal candidate will have deep expertise in AWS, AI/GenAI technologies, and open-source AI frameworks/LLMs, with hands-on experience in building scalable, secure, and innovative solutions.
Key Responsibilities
Architect AI Ops Solutions: Design and implement AI-driven operational frameworks for predictive analytics, anomaly detection, and automated remediation.
Cloud Architecture Leadership: Build enterprise-grade solutions leveraging AWS services.
Open-Source AI Frameworks: Implement MLOps pipelines using embeddings, fault detection models, LangGraph, and vLLM.
Advanced AI Development: Hands-on experience with LangChain, LangFuse, Llama 3.2 LLM, and RAG-based architectures.
Agentic AI & MCP: Drive implementation of Agentic AI systems and Model Context Protocol (MCP), A2A for intelligent orchestration.
Collaboration: Work closely with cross-functional teams including Cloud Engineering, Data Science, and DevOps to deliver end-to-end AI Ops solutions.
Required Skills and Qualifications
Technical Expertise:
Hands-on experience with AWS services.
Working knowledge of AI/GenAI for autonomous networks.
Proficiency in AWS AI (SageMaker, Bedrock, Comprehend )
Strong knowledge of open-source MLOps technologies (embeddings, fault detection models), LangGraph, vLLM.
Hands-on experience with LangChain, LangFuse, Llama 3.2 LLM, and RAG architectures.
Experience in Agentic AI implementation and MCP, A2A.
Experience:
Minimum 8+ years in enterprise cloud architecture, with at least 3+ years in AI Ops and GenAI solutions.
Soft Skills:
Strong analytical and problem-solving skills.
Excellent communication and stakeholder management abilities.
Education:
Bachelor's or Master's degree in Computer Science, Engineering, or related field
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