Support Engineer

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 Ownership

• Own all support tickets for designated clients from creation through resolution at L1–L2 complexity
• Develop deep expertise in each client’s product configuration, integrations, payroll rules, and country-specific compliance
• Attend MBRs/QBRs for assigned clients, presenting ticket trends, root cause themes, and improvement actions
• Maintain client artifacts: wage type catalogs, data dictionaries, and configuration guides
• Engage BAU team members for country-specific payroll expertise while retaining full ticket ownership

Investigation & Resolution

• Identify 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 day
• Proactively validate deployment changelogs and release notes for impact on assigned client configurations

Knowledge Building & AI Collaboration

• Author and maintain knowledge base articles for common issues and resolutions; every resolved ticket contributes to the KB and AI training data
• Review AI-suggested resolutions for assigned clients, validate or correct them, and provide structured feedback
• Tag 100% of resolved tickets with structured resolution data for AI learning

24/7 Coverage

• Participate in shift rotation for 24/7 coverage as scheduled
• Handle cross-client tickets during off-peak shifts when primary account owners are off-shift
• Follow structured shift handover protocols

Skills & Qualifications

Required Competencies

• Comfortable navigating payroll configuration, interface files, and configuration guides
• Able to triage issues and determine when L3 engagement is needed vs. independent resolution
• Comfortable working alongside AI tools; able to validate AI suggestions and provide structured feedback
• Professional client-facing communication skills; able to present in MBR/QBR settings
• Strong problem-solving with ability to trace issues from symptoms to root causes
• Proficient in YouTrack ticket management and query building

Experience & Education

• Bachelor’s degree in IT, Business, HR, or equivalent professional experience in SaaS support or payroll operations
• Minimum 2 years in SaaS product support, HRIS support, or payroll operations
• Multi-country payroll experience preferred
• Candidates from implementation, compliance, or BAU backgrounds with strong analytical skills will be considered

SMART Goals

SLA Compliance

• Specific: Achieve and maintain 95% SLA compliance on all owned tickets across all priority levels
• Measurable: Percentage of tickets resolved within SLA timeframes
• Achievable: Through effective prioritization, AI-assisted triage, and proper L3 escalation
• Relevant: Core service delivery commitment to assigned clients
• Time-bound: 95% or higher, ongoing from day 1

Client Ticket Volume Reduction

• Specific: Reduce ticket creation volume for assigned clients by 25%
• Measurable: Month-over-month ticket creation count for each assigned client
• Achievable: By identifying recurring issues, escalating root causes to L3, and working with Product teams on permanent fixes
• Relevant: Directly measures effectiveness of the root cause elimination approach
• Time-bound: 25% reduction within 90 days

Knowledge Base Contribution

• Specific: Author a minimum of 3 knowledge base articles per month for assigned client issues
• Measurable: Number of published KB articles
• Achievable: By documenting resolutions as articles during the normal resolution workflow
• Relevant: Feeds the AI learning pipeline and enables self-service
• Time-bound: 3 articles per month, ongoing from month 1

Client Training Completion

• Specific: Complete all training modules for assigned client configurations, compliance, and integrations
• Measurable: Training modules completed and competency verified
• Achievable: Through scheduled sessions with Compliance, Configuration, and BAU teams
• Relevant: Required to deliver effective dedicated account ownership
• Time-bound: 100% of modules completed within 60 days

AI Feedback Compliance

• Specific: Tag 100% of resolved tickets with structured resolution and root cause data for AI learning
• Measurable: Percentage of closed tickets with complete tags
• Achievable: Through consistent tagging workflow integrated into ticket resolution process
• Relevant: Powers AI auto-resolution improvement
• Time-bound: 100% compliance within 30 days

Bounce Rate

• Specific: Achieve a personal bounce rate below 10% on all tickets
• Measurable: Percentage of own tickets incorrectly categorized or bounced back
• Achievable: Through improved initial analysis skills and compliance training
• Relevant: Reduces resolution time and improves team efficiency
• Time-bound: Below 10% within 60 days