CALIBRE Systems, Inc., an employee-owned mission-focused solutions and digital transformation company, is seeking a Hybrid Senior Data Scientist / AI Data Engineer to support the development of AI-enabled applications and reusable data products within customer environments. This role combines hands-on retrieval-based AI engineering with data engineering, analytics, and governed data-product delivery. The successful candidate will extend AI Assistant and LLM capabilities into applications, support document ingestion and retrieval, and build curated datasets, pipelines, and data products using approved tools and access models. Responsibilities include AI enablement and retrieval-based application support, extending the AI Assistant and LLM to approved data domains and document sets, supporting data ingestion, OCR, embeddings, indexing, and vector-store use, adding Q&A, search, AI-assisted views, and source-cited answers to applications, using approved AI services, retrieval guardrails, and query guardrails, and validating AI features against acceptance criteria, test sets, and quality thresholds. Additional focus on data engineering and reusable data products includes delivering curated datasets, scheduled extracts, documented pipelines, and data products; supporting SQL, relational databases, data modeling, data quality, and RBAC; building applications, dashboards, analytics, AI views, and products with Superset/Python; using governed data and customer-provided catalog resources. Security, access, quality, and delivery responsibilities include applying role-scoped retrieval

CALIBRE Systems, Inc., an employee-owned mission-focused solutions and digital transformation company, is seeking a Hybrid Senior Data Scientist / AI Data Engineer to support the development of AI-enabled applications and reusable data products within customer environments. This role combines hands-on retrieval-based AI engineering with data engineering, analytics, and governed data-product delivery. The successful candidate will extend AI Assistant and LLM capabilities into applications, support document ingestion and retrieval, and build curated datasets, pipelines, and data products using approved tools and access models. Responsibilities include AI enablement and retrieval-based application support, extending the AI Assistant and LLM to approved data domains and document sets, supporting data ingestion, OCR, embeddings, indexing, and vector-store use, adding Q&A, search, AI-assisted views, and source-cited answers to applications, using approved AI services, retrieval guardrails, and query guardrails, and validating AI features against acceptance criteria, test sets, and quality thresholds. Additional focus on data engineering and reusable data products includes delivering curated datasets, scheduled extracts, documented pipelines, and data products; supporting SQL, relational databases, data modeling, data quality, and RBAC; building applications, dashboards, analytics, AI views, and products with Superset/Python; using governed data and customer-provided catalog resources. Security, access, quality, and delivery responsibilities include applying role-scoped retrieval