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Remote mid-level data role with broad AI/LLM requirements at a known employer increases competition.
Specialized data engineering and LLM/vector search expertise limits cross-industry transferability.
Explicit 5+ years plus mandatory Databricks, Snowflake, and LLM production experience enforces strict filters.
Design and build scalable AI/LLM data pipelines and production-grade retrieval augmented generation (RAG) systems including embedding, indexing, and semantic search.
Develop and optimize data engineering platforms and pipelines using Databricks, Apache Spark, Snowflake, Delta Lake, and Airflow for batch and streaming workloads.
Collaborate with ML, data science, and product teams to productionize AI capabilities focusing on reliability, observability, and cost optimization.
5+ years of experience in data engineering, software engineering, or distributed systems.
Strong programming skills in Python and/or Scala/Java and advanced SQL.
Hands-on experience with Databricks, Snowflake, Apache Spark, Delta Lake, Airflow, and cloud data platforms.
Practical experience building applications using Large Language Models (LLMs) or Generative AI.
Experienced in building scalable, reliable, and observable production data and AI systems incorporating LLM-related technologies like RAG, embeddings, vector search, and AI agents.
Skilled in complex distributed systems and data orchestration for batch and streaming AI/ML workloads with a strong understanding of evaluation and monitoring for AI quality and performance.
Able to work cross-functionally with engineering and product teams to move AI prototypes to scalable production deployments in a primarily remote and global team setting.