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Niche LLM+DB skills reduce pool, but generic senior software title and metro hiring raise applicant density.
High — specialized combination of agentic AI, Text-to-SQL, and deep database expertise.
High due to mandatory expert SQL, multi-database, LLM/RAG, cloud, and senior/staff level requirements.
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Design and implement Agentic AI systems using SQL for data retrieval, manipulation, and autonomous AI agent development.
Develop high-performance data pipelines, optimized SQL queries, and maintain database architectures for AI workloads.
Integrate AI agents with multiple relational databases and data warehouses, optimize query performance, and mentor team members on best practices.
Expert-level SQL proficiency including complex joins, CTEs, window functions, recursive queries, and query optimization.
Experience with multiple database platforms such as PostgreSQL, SQL Server, Oracle, MySQL, and cloud data warehouses (Snowflake, BigQuery, Redshift).
Proficiency in programming with Python, Java, or C#, and strong understanding of data structures and algorithms.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building AI agents integrated with relational databases and cloud data warehouses in enterprise environments.
Strong background in database internals, data modeling, and performance tuning at scale.
Technical expertise spanning software engineering, data engineering tools (Apache Spark, Airflow), API development, and cloud infrastructure (AWS, Azure, GCP).