We are Hiring
To help product teams ship with clarity, we are building Mayosana — AI-managed requirements, expert-reviewed delivery, and client-visible progress. If that mission resonates, we would love to meet you.
Careers
We’re always excited to meet great people
Even if you don’t see the exact role listed today, we review strong profiles and reach out when there’s a fit. Send your resume and a short note on what you want to build at Mayosana.
What to include
- - Your resume (PDF preferred)
- - Links to portfolio / GitHub / LinkedIn (if available)
- - What role you’re aiming for + location/timezone
- - A 3–5 line note on why you’re a great fit
We aim to reply to serious applications within 72 hours.
Frequently asked questions about AI software delivery
Basics for founders and detailed answers for engineering and ops leads — written in plain language. Bring harder questions to your expert review call.
Starter questions
Mayosana is an AI-managed software delivery platform where MayosanaAI creates structured requirements fast, and human experts own review, commitments, and shipped outcomes.
You start with an AI intake chat. MayosanaAI asks the right business + technical questions and drafts a structured scope (BRD/FRD-style). Then an expert review call validates assumptions, risks, and what will ship first.
You receive a proposal with milestone payments and an execution plan. Once activated, delivery runs sprint-by-sprint with client-visible tickets, demos, blockers, and approvals in the dashboard.
Pricing is milestone-based (outcome-based). You pay to unlock the next delivered outcome, not for open-ended hours. Each milestone maps to a demo-ready scope with clear acceptance criteria.
Yes. Your dashboard shows sprints, client-visible tickets, blockers, documents, meetings, payments, and support — so the platform becomes the shared source of truth.
For technical and operations leads
AI handles speed: requirement discovery, first drafts, structured outputs, and automation triggers. Humans handle accountability: review, final decisions, milestone commitments, and delivery quality.
Changes are classified (clarification, in-scope refinement, new feature, Phase 2). Anything that impacts cost/timeline is made explicit before it’s added to a milestone or sprint.
Admins control “publish to client” operations. AI outputs are visible and persisted internally, but client-visible milestones, tickets, and updates are designed to be admin-controlled.
Project data stays inside your project record and is governed by role-based access (client vs admin). It is not reused across projects for model training.
Support tickets are linked to a project, with threaded messages and attachments. Admins can reply, close/reopen, and keep a clear post-delivery audit trail.