AI Data Platform Lead

About the Position

AI Data Platform Lead

Location: Canada

Remote: Yes

Employment Type: Full-time

Position Overview

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.

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 integration back into the warehouse.
Own the AI/ML feature layer - feature engineering strategy and standards, training data pipeline design, feature store architecture, and model output integration - enabling predictive analytics across churn, pipeline health, and operational forecasting.
Design and govern the operational data and GPT context layer, including structured context feed design for GPT assistants, data freshness and access SLAs for AI use cases, and cross-departmental data reuse standards.
Lead the Data Warehouse Foundation build in partnership with the external consulting team - setting architecture standards, reviewing implementation against AI-first principles, and ensuring the five-wave build plan delivers a foundation that serves the full intelligence architecture.
Design and manage data ingestion, ELT/ETL, and orchestration pipelines across all source systems, ensuring reliability, performance, and cost efficiency.
Establish and enforce AI data engineering standards across the organization - prompt-adjacent data design, agent data access patterns, reusable pipeline components, and quality assurance processes.
Own data access policy design and least-privilege access controls in partnership with Security, ensuring data made available to AI systems is governed, auditable, and compliant.
Define data quality standards and monitoring processes for AI-consumed data, where quality failures have direct impact on model and agent performance.
Partner with the Principal Data and Integrations Architect on infrastructure design, ensuring data modeling and AI consumption requirements are incorporated into pipeline and architecture decisions from the start - not retrofitted after build.
Partner with the VP FP&A and Manager of BI & Data to ensure the semantic and metrics layers are technically sound and serve both AI use cases and reporting requirements.
Manage the AI Ops data architecture roadmap, translating business and AI use case requirements from all 11 departments into sequenced, prioritized technical work.
Maintain documentation and knowledge transfer standards for all data architecture, pipelines, and integration patterns - ensuring AI Ops-built infrastructure is reusable, auditable, and not dependent on any single individual.
Collaborate with the AI Agent Engineer and GPT & AI Systems Lead to ensure data infrastructure supports agent orchestration, retrieval-augmented generation, and multi-step reasoning workflows.
Define the roadmap for data science and AI data work in partnership with the VP of AI Operations. All roadmapping is managed within AI Operations.
Evaluate and recommend data tooling, frameworks, and platform components in alignment with AI Ops' technology-agnostic, build-for-leverage approach.
Other duties as assigned.

Required Qualifications

Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related technical field required.
7–10 years of experience in data engineering, data architecture, or a related technical function, with at least 3 years focused on AI or ML data infrastructure.
Deep expertise in modern data stack technologies - Snowflake required; experience with dbt, Airflow or equivalent orchestration, and ELT/ETL pipeline design.
Demonstrated experience designing data architecture for AI consumption - including vector databases, embedding pipelines, RAG systems, or feature stores - not only for BI and reporting.
Strong data modeling skills across multiple paradigms: dimensional modeling, normalized models, and AI-optimized schemas for agent and model consumption.
Experience building and operating real-time or near-real-time data pipelines for operational AI use cases.
Proficiency in Python and SQL; experience with cloud data infrastructure on AWS required.
Experience designing data access patterns and governance controls for AI systems, including least-privilege access, audit logging, and AI-specific data security considerations.
Demonstrated ability to own cross-functional technical programs - translating requirements from multiple business domains into coherent, prioritized data architecture decisions.
Strong communication skills with the ability to make complex data architecture decisions legible to non-technical executives and cross-functional stakeholders.
SaaS industry experience required.

Preferred Qualifications

Experience in private equity-backed SaaS organizations.
Experience with agentic AI frameworks - LangGraph, Mastra, or equivalent - and the data infrastructure requirements they create.
Experience building or operating RAG architectures at production scale, including vector store selection, chunking strategy, retrieval optimization, and evaluation.
Experience with agent memory architectures and state persistence design for multi-step AI workflows.
Familiarity with AI governance and compliance requirements for data used in automated decision-making.
Experience supporting investment board or executive-level AI progress reporting from a technical infrastructure perspective.
Experience with Tines or equivalent no-code/low-code orchestration platforms for simple agent pipelines.
Exposure to contract lifecycle management, legal tech, or professional services data domains.

We Offer

Agiloft offers a comprehensive benefits package for US employees including but not limited to the following:

Medical, dental, and vision insurance
Short term and long-term disability
Life insurance and AD&D
Supplemental life insurance (Employee/Spouse/Child)
Health care and dependent care Flexible Spending Accounts
401(k) with company match
Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non- overtime eligible) position.
Paid parental leave
Voluntary benefits including pet insurance

About the Company

Ensuring a diverse and inclusive workplace is our priority. We are committed to an environment of acceptance where you are free to bring your full self to work. All employment decisions at Agiloft are based on business needs, job requirements, and individual qualifications without regard to race, color, religion or belief, national or social ethnic origin, sex, age, sexual orientation, gender identity and/or expression, parental status, marital status, Veteran status, or any other status protected by the laws or regulations in the locations where we operate. If you have a need that requires accommodation during the recruiting process, please let us know by contacting Director, Talent Acquisition, Brad Toothman at [email protected].

Applicants from underrepresented groups such as minorities, veterans, or individuals with disabilities encouraged to apply.

Applications will be reviewed as submitted. There will be no application deadline for this opportunity.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.