Product Manager - AI-Driven Ops & Automation (Equity)

Daisy; New York (NY); On-site; USD 80,000 - 130,000; Full time

Job summary

Daisy, a full-stack, AI-native property management company in NYC, is seeking a hands-on Product Manager who works beside operations and engineering to fix real work. You’ll map workflows, quantify gaps, prototype AI solutions, and ship changes with FDEs.

We're looking for an early-career, resourceful candidate who uses AI daily, builds small tools, and would rather ship a rough automation this week than wait for a perfect spec next month.

Qualifications

• 3+ years of experience in a relevant role.
• Strong process mindset and ability to identify repeatable patterns in messy work.
• Proficiency with data and ability to build clear narratives from data (SQL or BI tools).
• Demonstrated hands-on AI usage in work: prompts, prototypes, scripts, or AI tools.

Responsibilities

• Embed with operations to map end-to-end workflows and document time/quality leaks.
• Prioritize efficiency opportunities with data-backed sizing.
• Partner with FDEs to design, prototype, and ship AI-driven automations.
• Write clear specs and requirements for engineers and ops leads.
• Build and maintain dashboards and metrics to show impact of changes.
• Own SOPs and process docs and keep them up to date.
• Run rollout activities: training, readiness checks, adoption tracking, post-launch monitoring.
• Incorporate feedback from managers, boards, and residents into the roadmap.
• Prototype with LLMs and AI tools to validate ideas before engineering time.

Skills

3+ years experience

Process mindset

Data literacy

Hands-on AI usage

Strong written communication

Ownership mindset

Curiosity

Tools

SQL

Looker

PowerBI

Airtable

n8n

Retool

Cursor

Claude Code

Copilot

Job description

Daisy, a full-stack, AI-native property management company in NYC, is seeking a hands-on Product Manager who works beside operations and engineering to fix real work. You’ll map workflows, quantify gaps, prototype AI solutions, and ship changes with FDEs.

We're looking for an early-career, resourceful candidate who uses AI daily, builds small tools, and would rather ship a rough automation this week than wait for a perfect spec next month.