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Shared by 
about 2 months ago
Requirements and responsibilities
Principal AI Data Architect needed to design and scale enterprise-grade AI-ready data platforms. Requires 15+ years in data engineering/architecture with 3–5+ years building production AI/ML & LLM-era infrastructure. Expertise in lakehouse and data mesh (Databricks, Delta Lake, PySpark, Kafka, Spark Structured Streaming). Hands-on with vector stores, semantic models, knowledge graphs, and retrieval infrastructure. Strong LLMOps knowledge (MLflow, AI CI/CD, automated evaluation, monitoring). Experience in data governance, security, compliance in regulated industries; data access controls for AI agents. Proficient in Python, SQL, PySpark, Kafka, Databricks, Delta Lake, Snowflake, AWS, Docker, Kubernetes; LangChain, LlamaIndex, LLM APIs; vector DBs; MLflow, FastAPI, CI/CD pipelines, observability, metadata management.
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