I don’t just close tickets
I improve the system

Built the Customer Support function from the ground up and scaled it to approximately eight specialists across L1 and L2. Established the operating model, clarified responsibilities and created repeatable ways of working as the product and customer base grew.

• Led hiring, onboarding, coaching, workload distribution and quality review for a team of around eight specialists (4 L1 + 4 L2).
• Defined ticket intake, triage, severity, escalation, ownership, customer updates and closure practices.
• Developed internal workflows and SOPs to make support delivery more consistent and reduce reliance on individual knowledge.
• Worked cross-functionally with Engineering, QA, Product, Customer Success and Sales to coordinate customer-impacting issues and follow-up.

Investigated product behavior across APIs, integrations, customer-specific configurations and external dependencies—moving beyond the visible symptom to identify the likely cause and next action.

• Reproduced issues and compared expected versus actual behavior; inspected browser DevTools Network and Console, HTTP/HTTPS status codes, API requests and responses, JSON, logs and configuration.
• Used Postman, Swagger and Mixpanel during technical investigation; validated MongoDB data when relevant.
• Worked with integrations, White Label setups, CNAME/DNS, billing and pricing, account configuration and external services.
• Handled operational tasks not available through the product UI, including email replacement, account recovery, proxy replacement, email-integration diagnostics, data exports, brand replacement and settings resets.
• Separated product defects from setup, data, integration and external-dependency issues before escalation.

Prepared actionable engineering reports rather than forwarding incomplete customer descriptions. The goal was to give developers enough context to investigate efficiently and to verify the outcome with the customer.

• Documented reproduction steps, expected and actual behavior, impact, environment and relevant customer/workspace/campaign/prospect context.
• Collected links, logs, request details, screenshots or tracebacks when available, and identified dependencies that could affect reproduction.
• Tracked escalated issues, communicated progress to customers and verified fixes after release.
• Supported incident updates and release notes, and fed recurring problems and product gaps back to Product and Engineering.

Migrated Support from ClickUp to Pylon and developed workflows to reduce repetitive manual work. For the Pylon MCP connector, I collaborated with the Development team on setting up the connector, then focused on the Skills and workflow logic.

• Designed prompt-driven AI Skills to check whether a similar Engineering request already exists before creating a new task, helping reduce duplicate requests.
• Designed the task-creation flow from a customer conversation: carry over context, map details to the right ClickUp fields, set priority and tags, assign the appropriate owner, and write the created task link back to the corresponding field in Pylon.
• Built no-code/API-assisted workflows with Pylon, Make and ClickUp, including routing, task creation, field mapping and notifications.
• Continue to explore, develop and refine additional Skills using defined prompts and configuration.

Turned recurring investigations and team knowledge into reusable resources for both specialists and customers.

• Created 48 SOPs covering recurring support processes and troubleshooting patterns.
• Built and maintained more than 200 internal support case notes and two Help Centers.
• Structured knowledge sources and workflows for AI-assisted support; used recurring questions and knowledge gaps to improve coverage.
• Documented technical and operational procedures so work could be repeated, reviewed and transferred across the team.

Established reporting to understand support performance, customer experience, team workload and the contribution of AI-assisted support.

• Tracked CSAT (4.7/5), First Response Time (5 minutes), and Time to Resolution (3 hours for cases resolved by Support without Engineering escalation).
• Tracked a 12% team escalation rate, along with SLA compliance, communication quality, workload distribution and AI Agent performance.
• Prepared weekly Support reports for leadership and used trends to identify operational bottlenecks and opportunities for improvement.
• Contributed to AI-assisted Support workflows with an AI Agent Resolution Rate of 40%.

Connected customer-facing Support with product improvement and made multi-step White Label setup easier to execute and hand over.

• Shared structured product feedback and recurring issue patterns with Product, Engineering, Customer Success and Sales.
• Designed a White Label workflow from request intake through CNAME/DNS, configuration, billing/pricing and launch.
• Created DNS instructions and SOPs, supported troubleshooting and trained a senior specialist before transferring process ownership.
• Coordinated customer updates, release notes and incident communications across stakeholders.