AI Product Manager

Position: AI Product ManagerJob Grade: 6Department name: ProductRef code: REF-PRO-PM-092026Location: RemoteWorking Hours: 40 hours per weekReports to: Head of Innovation Job Summary:The AI Product Manager (AI PM) at Mercans plays a pivotal role in driving the vision, development, and delivery of AI-powered capabilities within the global payroll SaaS platform, including AI agents, conversational assistants, and intelligent automation. The AI PM leads strategic product planning, execution, and continuous improvement across these capabilities, ensuring alignment with business goals, customer needs, and market trends.In this senior leadership capacity, the AI PM translates vision into outcomes—owning roadmaps, defining innovative and differentiated features, driving product-led growth, and collaborating across Product, Engineering, Data Science, Operations, Business Development, and Support. The role is essential to building a scalable, intelligent platform that supports Mercans’ global expansion and industry leadership in payroll SaaS. Duties and Responsibilities:1. Product Strategy, Roadmap & Lifecycle ManagementOwn the product vision, roadmap, and delivery strategy for AI-powered capabilities across the platform, ensuring alignment with business objectives, customer priorities, and market trends.Translate business needs into epics, features, and backlog stories with clear acceptance criteria and traceability.Lead product delivery from discovery through release, ensuring quality, adoption readiness, and continuous feedback loops.2. Market Intelligence & USP DevelopmentAnalyze market trends, emerging AI technologies, competitive offerings, and customer feedback to identify product gaps and innovation opportunities.Define and deliver unique, forward-looking AI features that serve as clear unique selling points (USPs) and enhance Mercans’ market positioning.Collaborate with Marketing and Commercial teams to develop positioning frameworks, competitive battle cards, and feature differentiation collateral.3. AI Product Strategy & RoadmapOwn the strategic direction and roadmap for AI-powered capabilities across Mercans’ payroll platform, including AI agents that support payroll processing and conversational assistants that support employees, HR teams, and administrators.Translate business needs into clear product requirements for AI agent behavior, chatbot conversation flows, and automation logic, partnering with Data Science and Engineering to bring them to life.Prioritize and guide AI-powered features such as anomaly detection in payroll runs, predictive net pay variance, and intelligent error correction, working closely with Data Science to validate what’s feasible and valuable.Define what good performance looks like for AI agents and chatbots (accuracy, response quality, appropriate escalation to a human), and partner with Data Science to track it against SLA targets.Work with Engineering to define integration requirements so AI agents and chatbots connect cleanly with existing payroll, HR, time, attendance, and finance systems.Own the roadmap for evolving legacy rule-based processes toward more configurable, AI-assisted workflows, in partnership with Engineering.Collaborate with customer-facing teams to localize AI agent and chatbot behavior for different markets, white-label, and reseller use cases.4. Platform Scalability & ModularizationChampion the modularization of the platform, enabling scalable, repeatable delivery models for multi-tenant, enterprise, and mid-market clients.Define reusable product components, configuration templates, and conversation or automation building blocks to support faster deployments and higher configurability.Partner with Engineering and Implementation to architect scalable platform modules.5. Customer Success Enablement & PartnershipCollaborate with Customer Success/BAU Managers (CSMs) to ensure successful feature onboarding, usage optimization, and value realization.Participate in QBRs, onboarding workshops, and strategic client conversations to align roadmaps with client outcomes.Address client escalations tied to product functionality, proactively mitigating risks and ensuring follow-through on corrective actions.Provide enablement tools including training guides, troubleshooting workflows, usage dashboards, and support documentation.6. Partner & Ecosystem Product EnablementDefine product features and APIs to support white-label clients, resellers, and channel partners.Deliver integration toolkits, configuration documentation, and reusable interface specifications to support scalable partner implementations.Collaborate with Business Development to align platform capabilities with co-sell and co-delivery models.7. API, Integration & Ecosystem ManagementDefine business and technical requirements for third-party integrations (e.g., HRIS, WFM, ERP, finance systems).Manage the lifecycle of public APIs and embedded integrations, ensuring SLAs, security standards, and extensibility.Enable seamless client data exchange through configurable mapping, validation, and transformation rules.8. Implementation & Support Workflow AlignmentCollaborate with Operations and Support teams to align product features with real-world delivery processes.Identify product-led AI solutions, such as self-service chatbots, to reduce onboarding effort, eliminate manual configuration errors, and streamline client setup.Lead delivery of internal tooling or self-service capabilities to reduce operational burden on support and configuration teams.9. Change Management & Customer CommunicationDefine and execute structured change management processes for product releases, including internal readiness and client-facing communications.Provide impact assessments and rollout plans for high-impact features, including new AI capabilities or interface changes.Develop tailored change communications by feature segment and customer tier.10.AI Governance & Regulatory ReadinessEnsure AI features meet responsible-AI expectations (transparency, fairness, appropriate human oversight) across all jurisdictions supported by the platform, partnering with Compliance and Data Science.Maintain audit-readiness documentation for AI features, including traceability of requirements, QA artifacts, and release history.Monitor global AI regulatory developments (e.g., EU AI Act) and proactively plan for impact on product roadmaps.11. Security, Privacy & Data GovernanceCollaborate with Information Security and QCRM teams to embed privacy, encryption, and access controls into all AI product features.Support secure-by-design product practices including role-based access, configurable data retention, and audit trail capabilities.12. AI Innovation & AutomationLead ideation and delivery of AI-powered features such as AI agents, chatbots, predictive payroll error detection, and intelligent configuration recommendations.Partner with Data Science and Engineering to validate concepts, build MVPs, and track feature outcomes in production.13. Commercial & Financial AwarenessPartner with Business Development and Finance to assess monetization potential, feature packaging strategies, and cost-to-serve impact for new AI features.Support commercial teams with value propositions, usage-based pricing analysis, and business case development for premium AI features.14. Product Analytics & Outcome MeasurementDefine product success metrics including usage, adoption, retention, task completion time, and operational savings.Collaborate with Analytics teams to track real-time performance dashboards and provide post-release outcome reports to stakeholders.Integrate KPIs into roadmap prioritization and cross-functional review cycles.15. Operational Excellence & Product Delivery ProcessLead initiatives to improve sprint cadence, backlog hygiene, QA readiness, and stakeholder communication throughout the delivery lifecycle.Collaborate with the Engineering team to standardize sprint rituals, reporting templates, and risk registers.16. Innovation Pipeline GovernanceEstablish a structured process for ideation intake, feasibility scoring, stakeholder validation, and prioritization of innovative AI features.Maintain a curated innovation backlog with transparent status tracking and executive review touchpoints.Promote innovation culture through collaboration with internal teams, clients, and partners.17. Team Mentorship & Product LeadershipMentor junior product managers and associates, providing regular coaching, feedback, and growth plans.Champion internal product education through demo sessions, workshops, and onboarding content.Promote ownership, documentation discipline, and customer empathy within the product team.Education and Experience:Minimum Requirements:Bachelor’s degree in Business, Computer Science, Information Systems, or a related field from a recognized and accredited institution.Minimum 10 years of progressive experience in product management within B2B SaaS environments, with at least 5 years in a senior or strategic product leadership role.At least 3 years of experience as a product manager delivering AI-powered features (e.g., AI agents, chatbots, recommendation or automation capabilities), with a solid understanding of how these products are built, tested, and improved.Working knowledge of AI/ML concepts such as predictive modeling, natural language processing, and anomaly detection, sufficient to write clear requirements and collaborate effectively with Data Science and Engineering.Proven experience delivering compliance-sensitive product features across globally distributed platforms, including coordination with cross-functional teams (Compliance, QA, Security, Engineering).Working familiarity with APIs, platform architecture concepts, and data integration patterns with systems such as HRIS, ERP, and WFM, enough to write clear technical requirements.Demonstrated expertise in Agile product development, including backlog management, epic/story creation, sprint planning, and roadmap ownership.Ability to translate business and compliance requirements into scalable, customer-centric product solutions with traceable outcomes.Preferred Qualifications:Master’s degree (MBA or MS) in Product Management, Innovation, Technology Leadership, or Business Strategy.Familiarity with AI agents, conversational AI/chatbot design, and generative AI trends in enterprise SaaS.Experience working with cross-functional teams on model governance and responsible AI practices.Familiarity with data privacy and information security frameworks such as GDPR, ISO 27001, SOC 2, and data residency controls.Background in monetization strategy, including feature packaging, usage-based pricing, and cost-to-serve modeling.Prior success in building or scaling white-label SaaS products, reseller enablement models, and partner-centric platforms.Professional certifications such as PMP, SAFe® Product Manager/Product Owner (PM/PO), Certified Scrum Product Owner (CSPO), or Pragmatic Institute PMC certification.SMART Performance Goals – 12 Months:Roadmap Execution: Achieve ≥90% on-time delivery of roadmap features with full documentation, UAT coverage, and release readiness.USP Feature Development: Launch at least 3 innovative AI features with measurable market differentiation and commercial enablement collateral.AI Capability Launch: Deliver two AI-powered features (e.g., an AI agent or chatbot capability) that reduce manual configuration or increase payroll accuracy by 20% or more.Process Optimization: Lead two product delivery process improvement projects with documented increases in velocity, team satisfaction, or release quality.Innovation Governance: Establish and maintain a transparent innovation pipeline with at least 5 viable AI features presented to the executive team.Partner Enablement Success: Launch a partner enablement package, including API documentation, integration playbooks, and sandbox test kits, for Mercans’ white-label and channel partners. Achieve a 90% satisfaction rate in partner onboarding surveys and enable at least three partners to complete self-service integration.Support Ticket Volume Reduction: Identify the top five recurring product-related support issues and implement corresponding feature fixes, self-service improvements, or UI enhancements. Achieve a 20% reduction in related support ticket volume.Operational Impact Measurement Framework: Develop and deploy a product impact framework that quantifies operational benefits of major features (e.g., time saved, reduction in errors, increase in automation). Ensure this framework is applied to 100% of new high-impact features, and use insights to support product reviews and roadmap prioritization.