Product Support Engineer
Job Grade: 4Ref Code: REF_SUP_SE_042026Location: Remote — Americas (UTC-5 to UTC-3) or APAC (UTC+5 to UTC+8)Salary: Market CompetitiveReports to: Senior Support Engineer (Team Lead)Job Summary:The Support Engineer owns 2–3 named client accounts end-to-end, handling L1 and L2 complexity. This role works in partnership with AI (which handles initial triage and suggests resolutions) and with the L3 team (which takes over deep technical investigations). Support Engineers are the client relationship layer: they know their clients' configurations, attend their reviews, and author the knowledge base content that trains the AI. They participate in shift rotation for 24/7 coverage, with AI agents handling initial triage and low-complexity resolutions around the clock.Duties & Responsibilities:Client Account OwnershipOwn all support tickets for designated clients from creation through resolution at L1–L2 complexityDevelop deep expertise in each client's product configuration, integrations, payroll rules, and country-specific complianceAttend MBRs/QBRs for assigned clients, presenting ticket trends, root cause themes, and improvement actionsMaintain client artifacts: wage type catalogs, data dictionaries, and configuration guidesEngage BAU team members for country-specific payroll expertise while retaining full ticket ownershipInvestigation & ResolutionIdentify tickets requiring L3 investigation and escalate with structured context (symptoms, initial analysis, client impact, reproduction steps)Respond within SLA timelines: L1 within 1 hour, L2 within 4 hours, L3 within 1 business dayProactively validate deployment changelogs and release notes for impact on assigned client configurationsKnowledge Building & AI CollaborationAuthor and maintain knowledge base articles for common issues and resolutions; every resolved ticket contributes to the KB and AI training dataReview AI-suggested resolutions for assigned clients, validate or correct them, and provide structured feedbackTag 100% of resolved tickets with structured resolution data for AI learning24/7 CoverageParticipate in shift rotation for 24/7 coverage as scheduledHandle cross-client tickets during off-peak shifts when primary account owners are off-shiftFollow structured shift handover protocolsSkills & Qualifications:Required CompetenciesComfortable navigating payroll configuration, interface files, and configuration guidesAble to triage issues and determine when L3 engagement is needed vs. independent resolutionComfortable working alongside AI tools; able to validate AI suggestions and provide structured feedbackProfessional client-facing communication skills; able to present in MBR/QBR settingsStrong problem-solving with the ability to trace issues from symptoms to root causesProficient in YouTrack ticket management and query building.Experience & EducationBachelor's degree in IT, Business, HR, or equivalent professional experience in SaaS support or payroll operationsMinimum 2 years in SaaS product support, HRIS support, or payroll operationsMulti-country payroll experience preferredCandidates from implementation, compliance, or BAU backgrounds with strong analytical skills will be consideredSMART Goals:1. SLA ComplianceSpecific: Achieve and maintain 95% SLA compliance on all owned tickets across all priority levelsMeasurable: Percentage of tickets resolved within SLA timeframesAchievable: Through effective prioritization, AI-assisted triage, and proper L3 escalationRelevant: Core service delivery commitment to assigned clientsTime-bound: 95% or higher, ongoing from day 12. Client Ticket Volume ReductionSpecific: Reduce ticket creation volume for assigned clients by 25%Measurable: Month-over-month ticket creation count for each assigned clientAchievable: By identifying recurring issues, escalating root causes to L3, and working with Product teams on permanent fixesRelevant: Directly measures the effectiveness of the root cause elimination approachTime-bound: 25% reduction within 90 days3. Knowledge Base ContributionSpecific: Author a minimum of 3 knowledge base articles per month for assigned client issuesMeasurable: Number of published KB articlesAchievable: By documenting resolutions as articles during the normal resolution workflowRelevant: Feeds the AI learning pipeline and enables self-serviceTime-bound: 3 articles per month, ongoing from month 14. Client Training CompletionSpecific: Complete all training modules for assigned client configurations, compliance, and integrationsMeasurable: Training modules completed and competency verifiedAchievable: Through scheduled sessions with Compliance, Configuration, and BAU teamsRelevant: Required to deliver effective dedicated account ownershipTime-bound: 100% of modules completed within 60 days5. AI Feedback ComplianceSpecific: Tag 100% of resolved tickets with structured resolution and root cause data for AI learningMeasurable: Percentage of closed tickets with complete tagsAchievable: Through a consistent tagging workflow integrated into the ticket resolution processRelevant: Powers AI auto-resolution improvementTime-bound: 100% compliance within 30 days6. Bounce RateSpecific: Achieve a personal bounce rate below 10% on all ticketsMeasurable: Percentage of own tickets incorrectly categorized or bounced backAchievable: Through improved initial analysis skills and compliance trainingRelevant: Reduces resolution time and improves team efficiencyTime-bound: Below 10% within 60 days