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edisyl builds AI solutions that transform messy institutional data into decisions, workflows, and outcomes. The company emerged from 8 years of blockchain data infrastructure work (20+ chains, 700M+ resolved wallets) and now applies that capability to enterprises struggling to make their data work at scale without armies of analysts. They have active deployments with financial institutions and Interlochen, a proven architecture, and inbound demand from firms needing their solution.
This Product Manager role is a founding product partnership, not a traditional PM position. You'll own the long-term product roadmap and translate the founder/CTO's vision into a sequenced, compounding plan that the engineering team executes. The company is building a new product surface—public knowledge packs with private company overlays—and the hard product questions (provenance, public/private boundaries, version propagation, consumer-facing vocabulary) are still being defined. You need to drive these from fuzzy to decided, pressure-test vision against market signals, and maintain continuous customer discovery.
Key responsibilities include: owning the roadmap and driving alignment across leadership and team; running continuous customer and market discovery with active users; driving open product-architecture decisions to resolution; thinking through edge cases and product details before engineering picks them up; defining and prioritizing what gets built; and partnering closely with engineering, data science, sales, and customer success.
Success in year one means strong product retention and net revenue retention, materially reduced time-to-value for customers, a growing roster of recognizable logos, and proof that the enterprise product motion is real and compounding. You'll be expected to live in AI tools daily (Claude Code, etc.), understand the rough edges of what's possible now, and obsess over making dense technical capabilities feel effortless for non-AI-native users.
You should have ~7+ years in product with senior end-to-end ownership of a product line, a track record of owning roadmaps and being accountable for adoption/retention/growth outcomes, experience shipping products where simplicity or ease-of-adoption was the core challenge, and real AI/product adoption experience inside large organizations. You'll work closely with engineering and data science on technical products without needing infrastructure translated.
