AI Architect
Hybrid · Dallas, Texas, United States
Job Summary
AI Architect role to design and lead enterprise-scale AI/ML/Generative AI solutions on AWS/Azure, with Copilot as the UX layer. Responsibilities include end-to-end architecture from data ingestion to deployment and monitoring, integration with legacy systems, governance and compliance, scaling through MLOps, and guiding technology decisions across cloud platforms. Key focus areas include RAG pipelines, vector databases (e.g., Pinecone, FAISS, Milvus, Azure OpenAI/Search, OpenSearch), Agentic AI with multi-agent orchestration, and enabling enterprise use cases like Copilot-integrated workflows and automated task execution. Leadership responsibilities include mentoring data scientists, ML engineers, and data engineers, and collaborating with business/product teams to translate requirements into AI-driven solutions. Technical stack coverage includes Docker/Kubernetes, CI/CD, AWS/Azure ML tooling, feature stores, real-time/batch data pipelines, LLMs, PyTorch/TensorFlow.
Required Qualifications
- 10+ years experience in AI/ML/Architectural leadership
- Experience designing end-to-end AI/ML solutions on AWS and Azure
- Strong background in RAG (Retrieval-Augmented Generation) and Agentic AI architectures
- Experience with MLOps/LLMOps, CI/CD, model versioning, and observability
- Proficiency with vector databases and real-time/batch data pipelines
- Experience with AI governance, data privacy, and explainability
- Strong leadership and collaboration skills, mentoring data scientists and engineers
- Experience with designing scalable cloud-native AI platforms on AWS/Azure
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