Overview

Senior AI Lead – Document, Conversational & Data Intelligence

Responsibilities

• EDMO is hiring a Senior AI Lead to own and scale our AI stack across document intelligence, conversational intelligence, and data intelligence. You will turn prototypes into robust, production-grade capabilities that integrate deeply with customer systems and meet strict standards for scale, reliability, and security.
• You will work closely with product and engineering leadership, lead a small high-performing AI team, and directly influence how universities and institutions experience EDMO's platform.
• AI Strategy & Architecture
• Define and own the end-to-end AI architecture across document, conversational, and data intelligence.
• Design multi-tenant, cloud-native AI services optimized for performance, cost, and reliability.
• Establish standards for prompt engineering, tool/agent orchestration, RAG, fine-tuning, evaluation, and monitoring.
• Translate product requirements into clear technical designs, milestones, and delivery plans.
• Document Intelligence
• Lead design and implementation of document understanding pipelines for transcripts, forms, financial docs, policies, and knowledge bases.
• Build capabilities for OCR, layout analysis, entity extraction, classification, validation, and summarization.
• Implement retrieval-augmented generation over large document corpora, including indexing, chunking, and relevance tuning.
• Define quality metrics and automated evaluation suites to continuously improve accuracy, robustness, and latency.
• Conversational Intelligence
• Own the architecture of production-grade chat and voice assistants across web, mobile, and telephony channels.
• Design agentic workflows combining LLMs, tools/APIs, memory, and business rules to support complex student and staff journeys.
• Implement guardrails, policies, and UX patterns to minimize hallucinations and ensure safe, compliant responses.
• Set up a rigorous evaluation framework for conversation quality, containment, user satisfaction, and escalation performance.
• Customer System Integrations
• Architect and oversee integrations with customer CRMs, SIS, telephony, and data platforms (e.g., Salesforce, contact centers, data warehouses).
• Define API and event-driven integration patterns for both real-time and batch scenarios.
• Ensure AI features respect tenant boundaries, roles/permissions, and customer-specific configurations.
• Partner with solutions/implementation teams to make deployment repeatable, configurable, and maintainable across institutions.
• Data Intelligence & Analytics
• Collaborate with data engineering to design data models and pipelines that power AI features and insights.
• Lead development of models and heuristics for scoring, routing, prioritization, and personalization based on behavioral and conversational signals.
• Define and maintain dashboards and KPIs for AI performance, adoption, and business impact.
• Drive an experimentation culture with A/B tests, staged rollouts, and data-driven iteration.
• Production, Scale & Security
• Ensure all AI services meet enterprise standards for uptime, resiliency, and observability.
• Define and enforce best practices for logging, tracing, alerting, and model/service health monitoring.