Product Manager Ticketing & IT Solutions

HR POD - Hiring Talent Globally

Job Location:

Lahore - Pakistan

Monthly Salary: Not Disclosed

Posted on: 10 hours ago

Vacancies: 1 Vacancy

Job Summary

Requirements:

Degree in Computer Science AI IT or related technical field.
2-4 years of PM experience including Business SaaS or Business workflows/automations products.
Ability to translate ambiguous problems into well-structured workflows solutions and shipped features.
Strong attention to detail workflow logic edge cases and customer with APIs data models systems design and workflows/automations.
Bias toward action thrives in ambiguity loves technology owns the outcome hungry to learn.
Excellent communication & collaboration skills.
Experience with Ticketing/ITSM Systems or IT Systems AI/Copilot workflows or fast-paced work environments.

Responsibilities:

Build core ticketing workflows (creation routing assignment SLAs collisions approvals lifecycle stages) with a strong focus on usability edge cases intelligence and productivity.
Translate ambiguous requirements into clear product specs and deliverables in close collaboration with engineering.
Prioritize foundational gaps and define the path from MVP to a complete ITSM ticketing system.
Work with senior PMs to integrate core ticketing workflows with AI copilots and autonomous agents.
Participate in testing and evaluating AI-driven features (intent recognition suggested actions automated resolution).
Ensure all AI features remain intuitive safe and predictable for IT teams.
Conduct user interviews shadow workflows and analyze pain points to identify unmet needs and delight factors not just feature requests.
Document real problems hypotheses and opportunities before proposing solutions.
Study competitive tools to identify market patterns and opportunities for differentiation.
Ship in short cycles (MVPs in weeks) validating ideas quickly through wireframes prototypes AI-driven drafts and early customer feedback.
Collaborate closely with engineering to experiment refine and iterate without compromising quality.
Monitor qualitative and quantitative feedback loops to enable fast course corrections.
Maintain clear product briefs tickets and success metrics for each feature.

Requirements: Degree in Computer Science AI IT or related technical field.2-4 years of PM experience including Business SaaS or Business workflows/automations products.Ability to translate ambiguous problems into well-structured workflows solutions and shipped features.Strong attention to detail wor...

Requirements:

Degree in Computer Science AI IT or related technical field.
2-4 years of PM experience including Business SaaS or Business workflows/automations products.
Ability to translate ambiguous problems into well-structured workflows solutions and shipped features.
Strong attention to detail workflow logic edge cases and customer with APIs data models systems design and workflows/automations.
Bias toward action thrives in ambiguity loves technology owns the outcome hungry to learn.
Excellent communication & collaboration skills.
Experience with Ticketing/ITSM Systems or IT Systems AI/Copilot workflows or fast-paced work environments.

Responsibilities:

Build core ticketing workflows (creation routing assignment SLAs collisions approvals lifecycle stages) with a strong focus on usability edge cases intelligence and productivity.
Translate ambiguous requirements into clear product specs and deliverables in close collaboration with engineering.
Prioritize foundational gaps and define the path from MVP to a complete ITSM ticketing system.
Work with senior PMs to integrate core ticketing workflows with AI copilots and autonomous agents.
Participate in testing and evaluating AI-driven features (intent recognition suggested actions automated resolution).
Ensure all AI features remain intuitive safe and predictable for IT teams.
Conduct user interviews shadow workflows and analyze pain points to identify unmet needs and delight factors not just feature requests.
Document real problems hypotheses and opportunities before proposing solutions.
Study competitive tools to identify market patterns and opportunities for differentiation.
Ship in short cycles (MVPs in weeks) validating ideas quickly through wireframes prototypes AI-driven drafts and early customer feedback.
Collaborate closely with engineering to experiment refine and iterate without compromising quality.
Monitor qualitative and quantitative feedback loops to enable fast course corrections.
Maintain clear product briefs tickets and success metrics for each feature.