LLM Application Engineer
Core
Design and implement analytics pipelines using LLMs to extract patterns, cluster conversations, and generate insights from large-scale chat data.
Role type
LLM Application Engineer (Conversational AI Analytics)
Builds
Analytics pipelines, dashboards, and reporting artifacts for usage trends and user behavior.
Domain
Conversational AI, Analytics, Data Engineering
Deliverable
production ML models | dashboards & analysis
Required skills
Python, LLM prompt engineering, HDBSCAN, text embeddings, cloud-native orchestration, data pipeline development, clustering algorithms, dimensionality reduction, automated testing, data visualization
Preferred skills
Experience with object storage, search engines, relational databases, semantic similarity tasks
Technologies
Python, HDBSCAN, embedding models, cloud-native orchestration, object storage, search engines, relational databases
Responsibilities
Design and implement analytics pipelines for conversation data; Develop facet extraction approaches using LLMs; Build dashboards and reporting artifacts; Architect and optimize hierarchical clustering pipelines; Build and maintain data pipelines for ingesting and analyzing datasets; Develop evaluation frameworks to measure clustering quality and pipeline correctness.
Seniority
Mid-level, hands-on IC