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Tier-1 brand, remote role, mid-level generalist title, and metro applicant pool increase competition.
Specialized LLM, RAG, and vector-search expertise creates strong domain bias limiting easy cross-industry transfer.
Explicit 5+ years plus mandatory Databricks/Snowflake/Spark and LLM/tooling experience raises filter strictness.
Design and build scalable data and AI platforms/pipelines for training, inference, and retrieval workloads involving LLMs and Generative AI.
Develop production-grade RAG systems and AI applications with semantic search, vector retrieval, and agentic workflows integrating with multiple teams.
Ensure data quality, governance, monitoring, and optimize large-scale batch and streaming data workflows using Databricks, Spark, Snowflake, and Airflow.
Minimum 5+ years of experience in data engineering, software engineering, distributed systems, or related fields.
Proficient in Python and/or Scala/Java, advanced SQL; practical experience with Databricks, Snowflake, Apache Spark, Delta Lake, and Airflow.
Experience building applications using LLMs or Generative AI and understanding of RAG architectures, vector databases, semantic search, and retrieval.
Work Experience Required: 5+ years data engineering or related; Location: 100% remote across India; Notice Period: Not explicitly mentioned in the JD.
Experienced in designing large-scale, reliable, and observable data platforms supporting AI/ML workloads combining batch and streaming data.
Skilled in building production-ready AI systems with knowledge of LLM evaluation frameworks, AI observability, and vector search databases.
Comfortable working in cross-functional teams to deploy scalable AI solutions, with hands-on experience in cloud data ecosystems like Snowflake and Databricks.