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Niche senior role requiring LLM and finance-operations expertise, reducing candidate density.
Role requires combined finance operations, data engineering, and production LLM expertise, so cross-industry transferability is low.
Explicit 8+ years requirement plus mandatory production LLM, finance controls, and specific stack makes filters strict.
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Lead the design, deployment, and operational management of AI agents that optimize finance processes within QAD's ERP ecosystem.
Own the finance semantic data layer and integrate financial context with BigQuery datasets to enable correct AI agent reasoning.
Build and maintain AI agent lifecycle management including versioning, performance monitoring, incident response, risk management, and finance organizational training on AI workflows.
Minimum 8 years of professional experience including hands-on building/managing LLM-based agents in production, finance operations, and data engineering.
Proficiency in BigQuery, dbt, Fivetran, SQL, Python, and LLM orchestration frameworks.
Deep knowledge of financial controls, audit requirements, and finance operational process flows.
Work Experience Required: Minimum 8 years explicitly mentioned.
Experienced at bridging finance teams and technical implementation to deploy agent-driven autonomous workflows in finance operations.
Strong background combining finance operations, data engineering, AI/ML systems, and operational risk management of AI agents.
Comfortable owning end-to-end AI agent lifecycle including architecture design, process reengineering, training, and controls in a regulated environment.