AI Data Platform Lead

As the most trusted global leader in data-first contract lifecycle management (CLM) software, Agiloft helps organizations manage the end-to-end process of proposing, negotiating, signing, and leveraging contracts using our flexible Data-first Agreement Platform (DAP). With contract data as the foundation, customers quickly and collaboratively reach agreement and leverage contract visibility to thrive with competitive advantage. Employing powerful, pragmatic artificial intelligence as a legal force multiplier, and robust integration capabilities as a data liberator, organizations around the world trust Agiloft’s certified implementers to deliver connected, intelligent, and autonomous solutions across the entire contract lifecycle.
Top analysts like Gartner, Forrester, and IDC agree, all showing Agiloft as a leader in the CLM space. Our no code platform is easily managed and administered by business users, which is why Agiloft is the contract you keep: nearly a full 100% of new customers are satisfied with their initial implementations, and some 97% of customers renew every year. Ours is a growing, vibrant, successful company that is at the forefront of a market that is becoming a must-have for all organizations.
We believe that the way to build the strongest, most vibrant place to work is to bring in individuals from all walks of life, and to support them in bringing their authentic selves to their day, every day. Our working philosophy is that “EX = CX”: when employee experience is excellent, so is customer experience. We support multiple Employee Resource Groups (ERGs), and offer a working environment that supports healthy work/life balance, including floating holidays and a quarterly, no-questions-asked wellness day.

Position Overview

The AI Data Platform Lead is the foundational technical role within AI Operations responsible for designing, building, and governing the cross-departmental data infrastructure that powers Agiloft's AI transformation. This role owns the full data engineering scope required to make the Data Warehouse Foundation serve not only business intelligence and reporting, but the complete spectrum of AI use cases — GPT assistants, AI agents, predictive analytics, real-time operational intelligence, and the contextual intelligence layer that underpins the organization's intelligent operating model.

This role is the prerequisite for all downstream data consumers — including BI and reporting functions — to operate effectively. The AI Data Platform Lead reports to the VP of AI Operations and is a core member of the AI Operations team. This role is allocated fully within AI Operations and is managed, roadmapped, and prioritized by the VP of AI Operations. Any allocation outside of the AI Operations-designated resource percentage requires explicit agreement with AI Operations leadership.

This role is distinct from and complementary to the Principal Data and Integrations Architect, who owns the infrastructure layer — DW architecture design, pipeline build and maintenance, source system integrations, and platform reliability. The AI Data Platform Lead operates at the layer above infrastructure: owning what the data means, how it is modeled for AI and analytics consumption, whether it is trustworthy and fit for purpose, and how it connects to the intelligence layer that GPT assistants, agents, and predictive models depend on. The analogy is direct: the Principal Data and Integrations Architect builds and maintains the roads. The AI Data Platform Lead owns where the roads go, what travels on them, and whether what arrives at the destination is clean, modeled correctly, and ready for AI consumption.

This is not a traditional data engineering or BI role. It sits at the intersection of data science, AI infrastructure, and data governance — requiring someone who understands that in an AI-first organization, data quality and data modeling are not reporting concerns. They are the foundation of every intelligent system the organization depends on.

Job Responsibilities

 
• Own the end-to-end data architecture for the Data Warehouse Foundation, designing for AI-first consumption across GPT assistants, AI agents, predictive models, and operational intelligence — in addition to BI and reporting.
• Lead data modeling across all 11 departments, designing canonical enterprise data models that serve cross-functional AI and analytics use cases without duplication or fragmentation.
• Design and implement the contextual intelligence layer — including RAG architecture, vector store strategy, knowledge base ingestion pipelines, and document and unstructured data processing — that powers Agiloft's enterprise knowledge system.
• Build and maintain the agentic data integration layer: real-time and near-real-time data access patterns, agent memory and state persistence design, orchestration data requirements, and agent output integra