Role Summary:

The Product Manager will lead the end-to-end development, deployment, and scaling of the O-EYE platform—an AI-driven solution built using NLP, Claude AI, and MCP (Model Context Protocol). This role is responsible for defining product vision, translating business needs into scalable AI capabilities, and ensuring successful delivery across client environments.

You will act as the bridge between business stakeholders, data/engineering teams, and client leadership to deliver a high-impact, intelligent platform that drives insights, automation, and decision-making.

Core Accountability:

Own the full product lifecycle:
Concept (evolving)→ Design → AI Model Integration → Build → Deploy → Scale → Optimize

Key Responsibilities:

Product Strategy & Vision

• Define and own the product roadmap for O-EYE, aligned with business goals and client needs
• Translate AI/ML capabilities (NLP, LLMs, MCP integrations) into practical, scalable product features
• Identify market opportunities within Higher Education and adjacent sectors
• Establish product positioning, value proposition, and differentiation

AI Platform Development

• Lead the design and development of AI-powered features leveraging NLP and Claude AI
• Oversee integration of MCP to enable contextual intelligence and extensibility
• Work closely with Data Engineers, ML Engineers, and Architects to ensure robust AI pipelines
• Define data requirements, model usage strategies, and feedback loops for continuous improvement

Product Delivery & Execution

• Own the end-to-end product lifecycle: ideation, design, build, test, deploy, and iterate
• Define and manage product backlogs, user stories, and sprint priorities
• Ensure timely delivery of releases with clear milestones and measurable outcomes
• Drive UAT, deployment planning, and client onboarding

Stakeholder Management

• Collaborate with internal leadership, sales, and delivery teams to align on priorities
• Engage with clients to gather requirements, validate features, and ensure adoption
• Act as the primary point of contact for product-related decisions and escalations

Platform & Deployment Strategy

• Define scalable deployment models (multi-tenant, cloud-native architecture)
• Ensure the platform supports integration with ERP systems (e.g., Banner SIS), CRM, and data ecosystems
• Drive standardization of reusable frameworks and components

Performance & Optimization

• Define KPIs and success metrics for product adoption, performance, and ROI
• Monitor platform usage, AI model performance, and user feedback
• Continuously refine features based on analytics and insights

Required Qualifications

• 4–5 years of experience in Product Management, with strong exposure to AI/ML platforms
• Strong understanding of:
  
  • NLP pipelines
  • RAG architectures
  • Vector databases and semantic search
• Experience managing end-to-end product development and deployment

Preferred Qualifications:

• Experience in Higher Education systems
• Exposure to AI orchestration frameworks (MCP or similar patterns)
• Experience with cloud-native AI deployments
• Background in data platforms, analytics, or decision intelligence systems

Key Skills:

• AI Product Management (LLMs, NLP, GenAI)
• Strong technical depth with ability to work with engineers and data scientists
• Product lifecycle ownership (0 → 1 and scale)
• Strategic thinking with execution focus
• Stakeholder and client management
• Understanding of AI limitations, risks, and trade-offs