Jeevan Ramesh Jadhav

Though hired for a technical AI automation & blockchain role, independently drove end-to-end product management — requirements gathering, prioritization, roadmap decisions, and stakeholder communication — alongside development, AI integration, and deployment work. Led end-to-end digital transformation of the company's client-facing platform, rebuilding it from a static site into a production AI- integrated product (dealcollab-ai. vercel. app), improving brand credibility and stakeholder confidence. Translated senior stakeholder requirements into structured product specifications, reducing cross-team miscommunication by maintaining a live requirements tracker across Agile sprints. Designed and deployed AI automation workflows that eliminated ~5 hrs/week of manual data processing, freeing team capacity for higher-value client work. Owned the full product lifecycle — discovery, design, build, deployment, maintenance — as sole product owner across 2 concurrent workstreams, leading product planning for a 5-person cross-functional team. Conducted process analysis across internal operations, identifying 3 automation opportunities; prototyped and validated solutions using LLM APIs with stakeholders before technical build. Built an admin analytics dashboard to track platform health, scaling Deal Collab to 117 users, 3,141 active proposals, and 3,143 proposal-matches; used it to surface EOI pipeline delays (18 pending 3+ days) as the top operational blocker.

Audited and restructured 15 AI/ML learning modules on a platform serving 45 M+ learners, improving content relevance for real- world product and engineering use cases. Identified 8 high-demand content topics (Agentic AI, Prompt Engineering, LLM APIs) through job-posting and keyword analysis; 3 were greenlit for production, directly shaping the content roadmap. Proposed and implemented a content taxonomy framework that reduced editorial review time by ~25% per module — adopted as a process standard by the full content team.