About this role
Technical Lead, AI Data Governance at Coupa Software, owning data governance and gateway strategy for GenAI and agentic applications. Ensures data flowing into AI tools is governed, trusted, and fit for purpose while enforcing API gateway policies that protect the company. Senior IC role partnering with Enterprise Data Management, AI Delivery & Execution, and InfoSec.
Must have
8+ years of related experience with at least 5 years as Data Product Manager or Technical Program Manager
Track record shipping AI/ML solutions end-to-end in an enterprise environment
Working knowledge of LLM application patterns including prompt engineering, RAG, embeddings, and agent frameworks
Solid grounding in data governance principles and frameworks such as DAMA-DMBOK or DCAM
Familiarity with API governance platforms and policy enforcement layers
SQL fluency sufficient to profile data quality directly against warehouse tables like Snowflake
Working familiarity with GDPR, CCPA, EU AI Act, and NIST AI RMF
Strong written communication skills for authoring policies and playbooks
Technologies
Responsibilities
Own the AI-readiness framework defining completeness, freshness, accuracy, lineage, consent, and source-of-truth for enterprise data assets
Drive extension of data catalog into AI asset inventory rating assets as AI-ready, AI-restricted, or AI-prohibited
Partner with Enterprise Data Management to ensure data quality refreshes flow into vector stores and RAG indexes
Author and maintain Coupa's AI data governance playbook covering acceptable use and data classification
Build and run intake and review for new AI use cases with five business day turnaround target
Translate compliance and regulatory requirements into operational standards for data and AI teams
Co-own the AI/API gateway defining governance policies, observability requirements, and controls for PII detection
Define gateway-level controls for prompt sanitization, content filtering, and prompt/response logging
Pair with AI engineers on data sourcing decisions and human-in-the-loop checkpoint requirements
Triage AI quality incidents tracing issues through gateway, RAG pipeline, and source records
Benefits
Amenities
Recruitment process
Senior individual contributor role reporting to Director, Data Governance
Partners daily with Enterprise Data Management, AI Delivery & Execution, and InfoSec
Embedded in AI Delivery & Execution team's planning rituals and architecture discussions
Connects metric library to AI consumers with governed metric definitions and testable lineage
Defines AI-aware data quality monitoring requirements
Defines observability and reporting for gateway usage, anomaly alerts, and per-model cost tracking
