Product Owner
Job Description:
Position Summary
The Product Owner is responsible for understanding business problems, identifying opportunities for improvement, and translating those needs into practical software solutions that create measurable value for Perform[cb], our internal teams, advertisers, and affiliate partners.
This role acts as a bridge between business stakeholders, users, design, engineering, data, and leadership. The Product Owner will gather context, analyze workflows, define requirements, prioritize development work, and help ensure that the final product solves the right problem in a simple, effective, and scalable way.
As Perform[cb] continues to expand its use of AI, automation, and data-driven decision-making, this role requires someone who is comfortable using AI tools to move faster. The ideal candidate can use AI to support research, documentation, prototyping, data exploration, workflow design, solution development, and product validation.
This role will also help identify opportunities where AI agents, automation, and intelligent workflows can reduce manual work, improve decision-making, increase consistency, and help teams operate more efficiently.
This is not a purely administrative backlog-management role. The ideal candidate is a hands-on problem solver who can understand how the business operates, identify where software can improve a process, and work with engineering to turn those ideas into useful products and features.
Key Responsibilities
Business Problem Solving & Product Discovery
Understand business problems, user workflows, operational pain points, and company goals.
Partner with the VP of Product, business stakeholders, and technology leaders to define product priorities aligned with company objectives.
Work with internal teams, advertisers, and affiliate partners to understand needs, gather feedback, and identify opportunities for improvement.
Analyze workflows and business processes to determine where software, automation, AI, or better data visibility can create value.
Translate ambiguous business problems into clear product opportunities, workflows, requirements, and success measures.
Evaluate product ideas based on business value, user impact, technical feasibility, available data, and expected ROI.
Identify opportunities to improve efficiency, automate manual work, increase revenue, improve partner engagement, and enhance campaign performance.
Software Solution Design
Translate business needs into practical software solutions that are simple, scalable, and aligned with user needs.
Create clear workflows, user stories, acceptance criteria, business rules, edge cases, and release requirements.
Think through how a feature should work from end to end, including user experience, data needs, system behavior, operational impact, and post-launch measurement.
Break large product ideas into smaller, manageable increments that can be delivered iteratively.
Collaborate with engineering, design, QA, and data teams to clarify requirements, resolve open questions, and make practical trade-off decisions.
Ensure that proposed solutions solve the underlying business problem, not just the surface-level request.
AI, Automation & Agentic Workflows
Use AI tools to accelerate product discovery, research, user-story creation, workflow mapping, documentation, analysis, and requirements development.
Create lightweight prototypes, mockups, workflow demos, or proof-of-concepts using tools such as Figma, ChatGPT, Claude, Cursor, Lovable, Bolt, Replit, no-code tools, low-code tools, or similar platforms.
Identify business workflows where AI agents, automation, or guided decision-support tools could reduce manual effort, improve speed, increase consistency, or improve business outcomes.
Help define the role of human oversight in AI-powered workflows, including when an AI system can act automatically, when it should recommend an action, and when a human should review before execution.
Work with engineering and data teams to design practical AI-enabled workflows, including inputs, outputs, permissions, guardrails, escalation paths, and success metrics.
Help define how AI-powered features should behave, including expected outputs, human review points, feedback loops, confidence thresholds, edge cases, and quality measurements.
Understand the limitations of AI systems, including false positives, hallucinations, inconsistent outputs, model drift, data quality issues, and the need for testing, validation, and ongoing monitoring.
Stay curious about new AI tools and identify practical ways they can improve product development, internal workflows, and business operations.
Data Analysis & Product Measurement
Use data to understand problems, validate assumptions, prioritize opportunities, and evaluate product performance after launch.
Define clear KPIs and success criteria for product initiatives before development begins.
Use dashboards, spreadsheets, reports, AI-assisted analysis, and available data sources to investigate trends and support product decisions.
Partner with data, engineering, and business teams to ensure required tracking, reporting, and measurement are in place.
Analyze product usage, operational metrics, campaign performance, partner behavior, funnel performance, and business outcomes to identify opportunities for improvement.
Present findings and recommendations in a clear, concise way for both technical and non-technical audiences.
Understand what questions need to be answered with data, even when someone else is helping pull the raw data.
Backlog Management & Requirements
Own and manage the product backlog, ensuring priorities reflect business value, urgency, user impact, and strategic alignment.
Write clear user stories, acceptance criteria, business rules, workflows, and edge cases.
Ensure requirements are well-defined, testable, and ready for development.
Collaborate with engineering to clarify questions before and during development.
Balance stakeholder requests with roadmap priorities, business impact, and development capacity.
Maintain clear documentation so stakeholders and development teams understand what is being built, why it matters, and how success will be measured.
Participate in backlog refinement, sprint planning, demos, retrospectives, and release planning.
Stakeholder Collaboration
Serve as a key point of contact for product-related questions, decisions, updates, and trade-offs.
Collaborate with internal teams including Product, Engineering, Marketing, Partner Development, Marketer Development, Account Management, Compliance, Finance, Operations, and Data.
Translate complex technical, data, or workflow concepts into clear business language.
Communicate priorities, timelines, scope changes, risks, and product decisions transparently.
Facilitate alignment between stakeholders when priorities conflict or requirements are unclear.
Gather feedback from users and stakeholders before and after launch to guide future improvements.
Execution & Delivery
Partner with design, engineering, QA, data, and business stakeholders to deliver high-quality product releases.
Review and validate product deliverables against requirements and acceptance criteria before release.
Test features from the user and business perspective to ensure they solve the intended problem.
Support go-to-market, training, documentation, rollout, and internal adoption activities when needed.
Monitor product performance after launch and identify opportunities for iteration and improvement.
Ensure product releases are practical, useful, measurable, and aligned with the business outcome they were designed to support.
Continuous Improvement
Use feedback, data, and product performance to continuously improve features and workflows.
Help improve product processes, documentation standards, discovery practices, and agile execution.
Stay current on product management, AI, automation, adtech, affiliate marketing, and performance marketing trends.
Promote a culture of experimentation, measurement, practical innovation, and continuous improvement.
Look for ways to make both the product and the product-development process faster, smarter, and more effective.
Qualifications
Experience as a Product Owner, Product Manager, Business Analyst, Solutions Analyst, or similar role. We are open to candidates with different experience levels if they demonstrate strong product thinking, business understanding, and the ability to turn problems into practical software solutions.
Strong ability to understand business problems, user workflows, operational pain points, and company goals.
Proven ability to translate business needs into clear product requirements, workflows, user stories, acceptance criteria, and development priorities.
Comfortable using AI tools such as ChatGPT, Claude, Gemini, Cursor, or similar tools to move faster in product discovery, research, documentation, prototyping, analysis, and solution design.
Ability to use AI tools, dashboards, spreadsheets, reports, and available data to investigate problems, identify trends, validate assumptions, and support product decisions.
Strong analytical mindset, with the ability to ask the right questions, interpret data, and connect product decisions to business outcomes.
Ability to create lightweight prototypes, mockups, workflow diagrams, or demos using tools such as Figma, AI prototyping tools, no-code/low-code platforms, or clear written documentation.
Strong communication skills, including the ability to explain business problems, proposed solutions, trade-offs, and requirements to both technical and non-technical audiences.
Strong organizational skills and the ability to manage priorities across stakeholders, engineering, design, and business teams.
Experience working with Agile, Scrum, Kanban, or similar product development processes.
Proficiency with Jira or similar product/project management tools.
Familiarity with Figma or similar design/prototyping tools is a plus.
Bachelor's degree in Business, Computer Science, Marketing, Data Analytics, or a related field preferred. Equivalent practical experience will also be considered.
Preferred Qualifications
Experience in adtech, martech, affiliate marketing, performance marketing, lead generation, mobile app marketing, SaaS, internal tools, workflow automation, or marketplace platforms.
Experience working on AI-enabled, data-driven, automation, recommendation, fraud detection, anomaly detection, optimization, or decision-support products.
Familiarity with AI agents, workflow automation, or agentic product concepts, including how AI systems can assist with research, recommendations, task execution, monitoring, and follow-up actions.
Experience using AI tools as part of daily work, not just conceptual familiarity with AI.
Experience with experimentation, A/B testing, cohort analysis, funnel analysis, or ROI measurement.
Experience working with internal tools or operational workflows used by sales, account management, finance, compliance, marketing, or operations teams.
Basic technical fluency, including understanding APIs, databases, event tracking, integrations, data flows, and software development trade-offs.
Experience working with dashboards, BI tools, spreadsheets, reports, or SQL-generated outputs.
Curiosity and hands-on willingness to test new AI tools, build prototypes, and find ways to make product development faster and better.
Ideal Candidate Profile
The ideal candidate is a practical, business-minded Product Owner who can operate between business, users, engineering, data, and leadership.
They are strong at understanding how a business process works, identifying where the pain points are, and designing software solutions that make the process better. They do not simply collect requests or manage tickets. They ask why the problem exists, who it impacts, what outcome matters, what data is available, and what the simplest effective solution should be.
They are comfortable using AI tools in their daily work to move faster and improve the quality of their thinking, documentation, prototypes, and analysis. They are curious about AI agents and automation, but also understand that AI-powered workflows need human oversight, guardrails, clear success metrics, and ongoing validation.
They should be especially strong at asking:
What business problem are we solving?
Who is affected by this problem?
What does the current workflow look like?
What would a better software solution look like?
What data do we need to make a good decision?
What can we automate?
What can AI help us do better?
Where do we need human review or approval?
How will we measure whether this worked?
What is the simplest version we can build to create value quickly?
This person should be hands-on, curious, organized, analytical, and comfortable working in a fast-moving environment where technology, AI, automation, and data are central to how the business grows.
The above job description is not intended to be an all-inclusive list of duties and responsibilities. The company reserves the right to assign or reassign duties and responsibilities as business needs require.