Product Manager, Post-Order UX & AI Automation

📍 Job Overview

Job Title: Product Manager, Post-Order UX & AI Automation

Company: Gametime United

Location: Remote (United States)

Job Type: Full-Time

Category: Product Management / Operations Technology

Date Posted: 2026-09-08

Experience Level: Senior/Staff/Principal Product Manager (5-10 years)

Remote Status: Remote Solely

🚀 Role Summary

• Drive product strategy and roadmap for post-order customer experience, focusing on AI-driven automation to enhance self-service and internal operational efficiency.

• Optimize post-purchase communications and ticket delivery processes to set clear expectations and minimize fan-related issues, directly impacting customer satisfaction (CSAT) and operational costs.

• Develop and implement AI/LLM-powered product features for both customer-facing self-service tools and internal Fan Operations agent-assist functionalities.

• Leverage data analysis, including SQL, to diagnose user pain points, measure key operational metrics (contact rate, handle time, cost to serve), and inform product decisions.

📝 Enhancement Note: This role sits at the intersection of Product Management, User Experience (UX), and Operations Technology. The emphasis on AI automation for both customer-facing self-service and internal support tooling indicates a strong focus on operational efficiency and cost reduction within a customer service context. The role is open to various levels, suggesting flexibility in hiring based on candidate expertise and the scope of responsibilities they can effectively manage.

📈 Primary Responsibilities

• Own the end-to-end roadmap for post-order customer journey, from order confirmation through ticket delivery and event attendance, with a focus on reducing friction and improving clarity.

• Design and execute strategies for post-purchase communications, ensuring timely, accurate, and proactive updates regarding orders, deliveries, and event changes.

• Develop and launch AI-powered self-service tools and conversational interfaces to empower customers to resolve common post-order issues independently.

• Build and enhance AI-driven tools for the Fan Operations team, including agent-assist capabilities, intelligent routing, automated triage, and knowledge retrieval systems to improve support efficiency and quality.

• Drive measurable improvements in key operational metrics such as customer contact rate, average handle time (AHT), customer satisfaction (CSAT), and overall cost to serve.

• Collaborate closely with Fan Operations leadership, Engineering, Data Science, Trust & Safety, and Supply teams to align product initiatives with broader business objectives and operational capabilities.

• Utilize data analysis and SQL to identify trends, diagnose customer pain points, and validate the impact of product initiatives on operational efficiency and customer experience.

📝 Enhancement Note: The responsibilities clearly outline a strategic product management function focused on operational excellence. The emphasis on AI and LLMs for both customer self-service and internal tooling suggests a significant opportunity to leverage cutting-edge technology for process optimization. The expectation to work with SQL and other data tools highlights the need for a data-driven approach to problem-solving and decision-making in this role.

🎓 Skills & Qualifications

Education: While no specific degree is mandated, a Bachelor's degree in Computer Science, Business, Engineering, or a related field is often preferred for Product Management roles.

Experience: 5-10 years of experience in product management, with a significant portion focused on post-purchase experiences, customer service operations, contact center technology, or marketplace environments.

Required Skills:

• Proven track record of successfully shipping product features that have demonstrably moved key business metrics (e.g., contact rate, CSAT, cost to serve).

• Strong understanding of customer service operations, support metrics (contact rate, handle time, CSAT, cost to serve), and their relationship to product design.

• Experience in developing and launching AI or LLM-powered product features, particularly in support, self-service, or agent-assist contexts.

• Proficiency in data analysis and diagnostics, with strong comfort in using SQL to query databases, identify user behavior patterns, and measure product impact.

• Excellent cross-functional partnership skills, with the ability to collaborate effectively with Engineering, Data, Fan Operations, Trust & Safety, and Supply teams.

• Ability to operate at various levels of scope, from hands-on execution to long-term strategic planning. Preferred Skills:

• Experience within a marketplace environment, specifically managing post-purchase customer journeys.

• Familiarity with various AI/ML models and their application in customer service scenarios.

• Experience with product development lifecycle management and agile methodologies.

• Understanding of UX design principles and their application in creating intuitive self-service and agent-assist tools.

📝 Enhancement Note: The requirements emphasize a blend of strategic product thinking, operational acumen, and technical understanding, particularly in AI and data analysis. The explicit mention of SQL and comfort with data-driven diagnostics suggests that candidates will need to be hands-on with data. The flexibility in title (Senior, Staff, Principal) implies that the depth of experience in these areas will be a key differentiator.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase case studies demonstrating successful product launches that directly improved customer satisfaction and/or reduced operational costs.

• Highlight examples where AI or automation technologies were leveraged to solve complex customer service or operational challenges.

• Provide evidence of data-driven decision-making, including examples of how data analysis (e.g., SQL queries, A/B tests) informed product strategy and execution.

• Demonstrate experience in managing the full product lifecycle, from ideation and strategy to execution, launch, and iteration. Process Documentation:

• Document a post-purchase workflow you have optimized, detailing the initial state, the changes implemented, and the resulting improvements in efficiency or customer experience.

• Illustrate how you have used AI or automation to streamline complex processes, such as customer issue resolution, ticket routing, or information retrieval.

• Present metrics and KPIs used to track the performance of operational processes and how product interventions influenced these metrics.

📝 Enhancement Note: For this role, a portfolio should strongly emphasize quantifiable results related to operational efficiency and customer satisfaction improvements, particularly those achieved through AI and automation. Candidates should be prepared to walk through specific examples of how they identified problems, designed solutions using data and AI, collaborated with engineering and operations teams, and measured the impact on key metrics.

💵 Compensation & Benefits

Salary Range: $169,000 - $250,000 USD per year. This range is provided by the company and reflects market data for similar roles in the United States. Actual compensation may vary based on individual skills, experience, and budget allocation.

Benefits:

• Comprehensive health, dental, and vision insurance plans.

• Generous paid time off (PTO) and holidays.

• Opportunities for professional development and continued learning.

• Potential for stock options or equity (common in tech startups).

• Remote work stipend to support home office setup.

• Access to company-sponsored events and team-building activities (virtual or in-person, as applicable).

Working Hours: Standard full-time hours are expected, approximately 40 hours per week. Flexibility may be offered, but the role requires availability to collaborate with teams across different time zones and respond to critical operational issues as they arise.

📝 Enhancement Note: The salary range is competitive for a senior-level Product Manager role in the US tech market, especially for a remote position with a focus on AI and operational impact. The benefits package is typical for a growth-stage tech company, with an emphasis on health and well-being, professional growth, and remote work support.

🎯 Team & Company Context

🏢 Company Culture

Industry: Live Events & Ticketing Technology. Gametime United operates within the dynamic and fast-paced live entertainment sector, providing a platform for discovering and accessing event tickets.

Company Size: The company description implies a growth-stage startup, likely ranging from 50-250 employees, as it supports a large number of events and has established platforms across multiple channels.

Founded: Founded in 2012, Gametime has a decade-plus history of innovating within the event ticketing industry.

Team Structure:

• The Post-Order UX & AI Automation team is a specialized product group.

• This role will report into a Director or VP of Product Management.

• Close collaboration is expected with Fan Operations leadership, Engineering teams (likely dedicated to this product area), Data Scientists, and potentially teams within Trust & Safety and Supply chain. Methodology:

• Data-driven product development, with a strong emphasis on A/B testing and quantitative analysis to validate hypotheses and measure impact.

• Agile development methodologies, likely Scrum or Kanban, for iterative product delivery.

• Focus on user-centric design, prioritizing both fan satisfaction and operational efficiency.

• Strategic roadmap planning, balancing short-term wins with long-term vision, especially concerning AI integration.

Company Website: Gametime.co

📝 Enhancement Note: Gametime's mission to "unite the world through shared experiences" suggests a company culture that values connection and engagement. For operations-focused product roles, this translates to a focus on seamless customer journeys and reliable service delivery. The growth-stage nature of the company means opportunities for significant impact and potential for rapid career advancement, but also requires adaptability and comfort with ambiguity.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned at a senior to principal level, indicating a need for significant product management expertise, strategic thinking, and a proven ability to drive complex initiatives independently. The scope involves owning a critical part of the customer lifecycle with a direct impact on operational costs and customer loyalty.

Reporting Structure: The Product Manager will likely report to a Director or VP of Product, working closely with engineering leads and operational counterparts in Fan Operations. This structure allows for both strategic direction from leadership and deep collaboration with execution teams.

Operations Impact: The role has a direct and measurable impact on Gametime's bottom line by reducing the cost to serve customers and improving fan satisfaction, which can lead to increased repeat business and positive brand perception. The focus on AI automation positions this role at the forefront of operational innovation within the company.

Growth Opportunities:

• Skill Advancement: Deepen expertise in AI/LLM product development, customer service operations, and data-driven product strategy.

• Leadership Potential: Opportunity to lead a critical product area, potentially mentoring junior product managers or taking on larger product portfolios within the company.

• Strategic Influence: Play a key role in shaping Gametime's approach to customer support and operational efficiency through technology.

• Career Progression: Potential to move into Staff or Principal Product Manager roles, or transition into leadership positions within Product or Operations.

📝 Enhancement Note: The flexibility in hiring level (Senior, Staff, Principal) suggests that candidates with exceptional strategic thinking and a strong track record in AI-driven operational improvements will be highly valued, potentially leading to accelerated growth opportunities within the company.

🌐 Work Environment

Office Type: Fully remote. This indicates a distributed workforce where collaboration and communication rely heavily on digital tools.

Office Location(s): While the role is remote, the company is based in the US, with a primary headquarters likely in San Francisco, CA, given its tech industry presence. The remote work is specified for the "United States," suggesting candidates should be based within the US.

Workspace Context:

• A highly collaborative digital environment, necessitating strong communication and asynchronous work practices.

• Access to a robust suite of collaboration tools (e.g., Slack, Zoom, Google Workspace).

• Emphasis on individual autonomy and accountability for managing one's work and schedule effectively.

• Potential for occasional in-person meetups or team offsites, though the primary mode of work is remote.

Work Schedule: While the core working hours are approximately 40 per week, the remote nature and the critical operational aspects of the role may require flexibility to attend meetings across different US time zones or address urgent issues that arise outside of standard business hours.

📝 Enhancement Note: As a remote-first company, Gametime likely fosters a culture of trust and results-orientation. Candidates should be comfortable with independent work, proactive communication, and leveraging technology to stay connected and productive. The "United States" location requirement for remote work is crucial for tax and employment law compliance.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screen: A conversation with a recruiter to assess basic qualifications, cultural fit, and interest in the role.

• Hiring Manager Interview: Discussion with the hiring manager (likely Director/VP of Product) to delve into experience, product strategy, and operational understanding. Expect questions about past product successes, handling of complex problems, and approach to AI/automation.

• Product/Technical Deep Dive: An interview focused on product sense, UX, and technical acumen. This may include a case study or product critique related to post-order experiences or AI in support. Proficiency with SQL and data analysis will likely be assessed here.

• Cross-functional Interview(s): Meetings with key stakeholders from Engineering, Fan Operations, and potentially Data Science to evaluate collaboration skills and ability to influence across teams.

• Final Round/Executive Interview: A discussion with senior leadership to assess strategic thinking, leadership potential, and overall fit with Gametime's vision.

Portfolio Review Tips:

• Quantifiable Impact: Clearly articulate the measurable business outcomes (e.g., % reduction in contact rate, % increase in CSAT, $ saved in cost to serve) for each project.

• AI/Automation Focus: Showcase specific examples of how AI or automation was integral to the solution and the resulting benefits.

• Data-Driven Narrative: Explain how data (SQL, analytics) was used to identify problems, shape solutions, and measure success.

• Process Optimization: Detail the "before" and "after" of any process improvements, highlighting the steps taken and the efficiency gains.

• Concise & Visual: Use clear, concise language and consider visual aids (diagrams, dashboards) to illustrate complex processes or results.

Challenge Preparation:

• Be prepared for a product sense or case study challenge that requires you to diagnose issues in a post-order journey and propose AI-driven solutions.

• Practice articulating your thought process, including how you would leverage data, define success metrics, and collaborate with engineering and operations.

• Think about common pain points in ticket delivery, order confirmations, and customer support for live events.

• Consider how AI/LLMs can be applied to automate responses, provide contextual information, or assist support agents.

📝 Enhancement Note: The interview process is designed to assess a candidate's ability to not only strategize but also execute and collaborate effectively within an operations-focused product role. A strong portfolio that clearly demonstrates quantifiable impact from AI-driven solutions will be critical for success.

🛠 Tools & Technology Stack

Primary Tools:

• Product Management Platforms: Jira, Confluence, Asana, or similar for roadmap planning, task management, and documentation.

• Collaboration Tools: Slack, Google Workspace (Docs, Sheets, Slides), Zoom for day-to-day communication and teamwork.

Analytics & Reporting:

• SQL: Essential for data extraction, analysis, and diagnostics.

• BI Tools: Tableau, Looker, Power BI, or internal dashboards for data visualization and reporting on key metrics.

• Product Analytics: Amplitude, Mixpanel, or similar for understanding user behavior within the product.

CRM & Automation:

• CRM: Salesforce or similar, though the specific CRM used by Fan Operations might be internal or specialized.

• AI/ML Platforms: Experience with or understanding of platforms and frameworks for building and deploying AI/LLM models (e.g., OpenAI API, Google AI Platform, custom ML frameworks).

• Customer Support Platforms: Zendesk, Intercom, or internal tooling for managing customer interactions and agent support.

📝 Enhancement Note: Proficiency in SQL and experience with BI/analytics tools are non-negotiable for this role, given the emphasis on data-driven decision-making and operational metric tracking. Familiarity with AI/LLM platforms is also a significant advantage, especially for building and deploying automated solutions.

👥 Team Culture & Values

Operations Values:

• Customer-Centricity: A deep commitment to improving the fan experience, even in the post-purchase and support phases, ensuring reliability and satisfaction.

• Data-Driven Decision Making: Relying on quantitative analysis and measurable outcomes to guide product strategy and operational improvements.

• Efficiency & Automation: Proactively seeking opportunities to streamline processes and leverage technology, particularly AI, to reduce costs and improve scalability.

• Cross-Functional Collaboration: A belief in working closely with diverse teams (Engineering, Operations, Data) to achieve shared goals.

• Innovation: Embracing new technologies like AI/LLMs to solve complex problems and drive competitive advantage.

Collaboration Style:

• Partnership-Oriented: Working closely with Fan Operations leadership to understand their challenges and co-create solutions.

• Engineering-Focused: Translating business needs and user problems into clear product requirements for engineering teams.

• Data-Informed: Regularly engaging with Data Scientists and analysts to leverage insights and validate hypotheses.

• Proactive Communication: Maintaining transparency and regular updates across all stakeholder groups, especially in a remote environment.

📝 Enhancement Note: The company culture likely values innovation and a results-oriented approach, with a strong emphasis on using technology to solve real-world operational challenges and enhance customer experiences. A candidate's ability to thrive in a collaborative, data-informed, and efficiency-focused environment will be key.

⚡ Challenges & Growth Opportunities

Challenges:

• Balancing Automation with Quality: Implementing AI and automation effectively without compromising the quality of customer support or creating new friction points.

• Data Integration & Availability: Ensuring access to clean, reliable data across various systems for accurate AI model training and performance analysis.

• Cross-Functional Alignment: Gaining buy-in and managing dependencies across multiple departments, each with its own priorities.

• Rapidly Evolving AI Landscape: Keeping pace with advancements in AI and LLM technology to ensure Gametime's solutions remain cutting-edge.

• Scalability: Designing solutions that can effectively scale with the growing volume of events and transactions.

Learning & Development Opportunities:

• AI/LLM Specialization: Gaining hands-on experience with cutting-edge AI technologies and their application in a real-world business context.

• Operational Excellence: Deepening understanding of customer service operations, contact center dynamics, and cost-to-serve optimization.

• Strategic Product Leadership: Developing strategic planning skills and influencing product direction at a senior level within a growing company.

• Industry Exposure: Working within the fast-paced live events and ticketing industry, gaining insights into unique operational challenges and opportunities.

📝 Enhancement Note: This role offers significant opportunities for growth by tackling complex operational challenges with advanced technologies like AI. The ability to navigate these challenges and drive impactful solutions will be a strong indicator of future leadership potential.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you used AI or automation to significantly improve a customer support process or reduce operational costs. What was the outcome?"

• "How would you approach reducing contact rate for post-order issues in a marketplace like Gametime? What data would you need, and what AI-driven solutions would you explore?"

• "Imagine a scenario where ticket delivery is delayed for a major event. How would you design the communication strategy and leverage AI to manage fan expectations and support inquiries?" Company & Culture Questions:

• "What excites you about Gametime's mission and the live events industry?"

• "How do you approach building relationships and driving alignment with cross-functional teams, particularly Fan Operations and Engineering?"

• "Describe your experience working in a remote-first environment and how you ensure effective collaboration and productivity." Portfolio Presentation Strategy:

• Problem -> Solution -> Impact: Structure your case studies around a clear problem statement, your proposed solution (emphasizing AI/automation and data), and the quantifiable impact achieved.

• Data Storytelling: Be prepared to walk through your SQL queries, data analysis, and how these insights informed your product decisions.

• Process Flow Visualization: Use diagrams to illustrate complex workflows and how your product interventions improved them.

• Focus on Metrics: Clearly define and present the key operational metrics you influenced and the magnitude of the change.

• AI/LLM Specifics: For AI-related projects, explain the type of AI/LLM used, the challenges in implementation, and the learning outcomes.

📝 Enhancement Note: Interview preparation should focus on demonstrating a strong understanding of operational metrics, a strategic approach to leveraging AI for efficiency, and the ability to collaborate effectively. Candidates should be ready to provide concrete examples from their past experience, supported by data and a clear narrative of impact.

📌 Application Steps

To apply for this Product Manager, Post-Order UX & AI Automation position:

• Submit your application through the Gametime United careers portal via the provided Greenhouse link.

• Tailor your resume and cover letter: Highlight specific experience with post-order customer journeys, AI/LLM product development, operational metrics (contact rate, CSAT, cost to serve), and data analysis (SQL). Quantify achievements wherever possible.

• Prepare your portfolio: Curate 2-3 key projects that best demonstrate your experience in driving operational efficiency and customer satisfaction through product, especially using AI and data. Be ready to present these with a focus on measurable outcomes.

• Research Gametime: Understand their business model, mission, and recent news to articulate your interest and how your skills align with their goals. Pay attention to their approach to customer experience and technology.

• Practice interview questions: Rehearse answers to common Product Management, AI/LLM, and operational strategy questions, focusing on providing structured, data-backed responses.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.