Head Of Artificial Intelligence (Pune)

Role Overview EDMO is seeking a Head of AI to define, build, and scale the companys end-to-end AI strategy across document intelligence, conversational intelligence, and data intelligence.This is a foundational leadership role responsible for transforming AI from a set of capabilities into a core competitive advantage for EDMO. You will drive the vision, architecture, and execution of AI systems that power mission-critical workflows for universities and institutions.You will partner closely with executive leadership, lead and grow a high-caliber AI team, and ensure all AI initiatives are production-grade, enterprise-ready, and aligned with business outcomes. Key ResponsibilitiesAI Vision, Strategy & Leadership - Define and own EDMOs AI vision, roadmap, and long-term strategy across all product lines - Identify high-impact opportunities where AI can drive revenue growth, efficiency, and differentiation - Act as the thought leader and internal evangelist for AI across the organization - Build, lead, and mentor a high-performing AI/ML team, setting technical and cultural standards - Partner with leadership on build vs buy decisions, investments, and AI roadmap prioritization Platform Architecture & Scalability - Own the design of a unified, scalable AI platform spanning document, conversational, and data intelligence - Architect multi-tenant, cloud-native systems optimized for scale, cost, performance, and reliability - Establish best practices for - LLM orchestration (agents, tools, workflows) - Retrieval-Augmented Generation (RAG) - Fine-tuning and model selection strategies - Evaluation, monitoring, and observability - Drive standardization to ensure reusability and consistency across AI capabilities Document Intelligence (Enterprise Scale) - Define the strategy and architecture for document understanding at scale - Oversee systems for - OCR and layout intelligence - Entity extraction, classification, validation - Knowledge ingestion and semantic search - Ensure high accuracy and robustness across diverse document types (transcripts, financial docs, - policies, etc.) - Establish evaluation frameworks, benchmarks, and continuous improvement loops Conversational & Agentic AI - Own the vision and architecture for AI-powered conversational experiences across chat and voice - Lead development of agentic systems combining LLMs, APIs, memory, and workflows - Ensure production readiness with - Guardrails and hallucination mitigation - Policy enforcement and compliance - Scalable conversation orchestration - Define and track metrics such as containment, resolution rate, CSAT, and business impact Data Intelligence & Decision Systems - Drive the development of data-driven intelligence layers powering personalization, scoring, and automation - Partner with data engineering to build robust data pipelines and feature stores - Define key business and AI metrics; establish dashboards and executive reporting frameworks - Lead experimentation strategy with A/B testing, staged rollouts, and continuous optimization Enterprise Integrations & Customer Deployments - Define scalable patterns for integrating with CRMs, SIS, telephony systems, and data platforms - Ensure AI capabilities are - Configurable and repeatable across customers - Secure, compliant, and tenant-aware - Work closely with implementation and customer success teams to ensure successful deployments and adoption Production Excellence, Security & Compliance - Ensure all AI systems meet enterprise-grade standards for uptime, resilience, and observability - Establish practices for - Logging, monitoring, alerting, and tracing - Model/version lifecycle management - Safe deployments (canary releases, rollback mechanisms) - Partner with security teams to ensure compliance with data privacy and regulatory standards Stakeholder & Customer Leadership - Engage directly with key customers to: - Understand complex requirements - Shape AI-driven solutions - Represent EDMOs AI capabilities and vision - Collaborate cross-functionally with product, engineering, sales, and leadership to align AI with business goals Required Qualifications - 10+ years of experience in software engineering, machine learning, or applied AI - 5+ years in leadership roles, building and managing high-performing AI/ML teams - Proven track record of scaling AI systems from concept to enterprise-grade production - Deep hands-on experience with: - LLMs, RAG, agents, and AI system orchestration - Document intelligence (OCR, extraction, classification, semantic search) - Conversational AI (chatbots, voicebots, agent assist systems) - Strong system design and architecture skills for distributed, cloud-native systems - Experience integrating with enterprise platforms (CRMs, telephony, data systems) - Solid understanding of AI evaluation, reliability, and governance frameworks - Familiarity with security, privacy, and compliance in Rol