Job Description

This hybrid engagement supports the development and production hardening of Natural Language Query (NLQ) systems, AI agents, and related applications powering talk-to-data experiences. The work focuses on improving NLQ accuracy and semantic understanding while building robust, scalable, and observable AI systems suitable for enterprise production environments.


This engagement requires senior-level software engineering depth, combined with AI evaluation and semantic modeling expertise, to translate research concepts into reliable, deployable systems.


Work/Project Scope:

  • Design, implement, and maintain production-grade AI services supporting NLQ and AI agent workflows.

  • Evaluate the NLQ system accuracy using quantitative and qualitative methods (precision/recall, semantic correctness, result equivalence).

  • Build automated evaluation pipelines and regression test suites integrated into CI/CD workflows.

  • D...

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