AI-Driven Performance Product Owner - Remote-Ready

confiemx-taadmin; Tijuana; On-site; MXN 420,000 - 660,000; Full time

Benefits offered by this job

Private Health Insurance

Life Insurance

Saving Funds and Voluntary Savings

Profit Sharing (PTU)

Vacation Days (above law)

Christmas bonus

Vacation premium

Job summary

Confie seeks a Product Owner to lead the vision, roadmap, and delivery of an internal performance management app for frontline operations. You will own data ingestion, metrics, and coaching workflows, working with agents, supervisors, and leaders to drive measurable outcomes and adoption.

You will coordinate with data engineering, analytics, and engineering teams to ensure data quality, governance, and safe deployment of AI-driven capabilities.

Qualifications

• 3–5 years in product management or related roles.
• Experience with insurance operations or call centers is preferred.
• Proficient in Agile (Scrum/Kanban) with end-to-end lifecycle ownership.
• Strong English (C1) and analytics literacy.

Responsibilities

• Define product vision, strategy, and roadmap aligned to frontline performance objectives.
• Translate operational needs into a prioritized backlog with user stories and metrics.
• Lead delivery from MVP to full deployment with phased rollout and change management.
• Own end-to-end features: goal setting, scorecards, workflows, coaching plans, dashboards.
• Establish analytics, instrumentation, and data contracts with cross-functional teams.

Skills

Product ownership

Agile delivery

Analytics fluency

Data fundamentals

API/Integration literacy

English communication

Education

Bachelor's degree

Tools

Snowflake

BI tools

CRM

Telephony

Job description

Confie seeks a Product Owner to lead the vision, roadmap, and delivery of an internal performance management app for frontline operations. You will own data ingestion, metrics, and coaching workflows, working with agents, supervisors, and leaders to drive measurable outcomes and adoption.

You will coordinate with data engineering, analytics, and engineering teams to ensure data quality, governance, and safe deployment of AI-driven capabilities.