Description
The Product Support Solutions Developer designs, builds, and maintains the technical infrastructure, tools, and automated workflows that power the customer support function. Combining technical development expertise with support operations and enablement, this role is responsible for architecting scalable internal tooling, engineering custom integrations, and leveraging AI agents/automations to drive operational efficiency, reduce resolution times, and elevate customer satisfaction.
Responsibilities
Custom Tooling & Integration Development
- Design, build, and maintain custom applications, scripts, and webhook integrations across core support systems (e.g., Zendesk, Jira, Salesforce Service Cloud, Domo, StatusPage).
- Architect and optimize API connections, custom middleware, and automated workflows to streamline ticket routing, data syncs, and escalations.
- Build custom UI components, apps, and macros within support platforms to enhance agent efficiency and desktop experience.
- Determine methods and procedures for new or undefined assignments, considering company objectives,to shape solutions.
AI Agent & Automation Implementation
- Lead the evaluation, development, and deployment of AI agents, LLM-powered assistants, and chatbots to automate tier-1 support interactions and internal agent assistance.
- Fine-tune AI agent prompt workflows, knowledge ingestion pipelines, and retrieval-augmented generation (RAG) models to improve self-service resolution rates.
- Monitor and continuously optimize AI agent performance, accuracy, and customer satisfaction metrics.
Support Operations & Tool Management
- Administer, configure, and optimize support systems, maintaining SLAs, routing rules, triggers, and automated workflows.
- Conduct regular quality, tag, and compliance audits across systems to ensure high data integrity and adherence to support processes.
- Assist Platform Operations and Support Leadership with outage communication tooling, incident escalation paths, and client updates.
Data Engineering, Analytics & Reporting
- Build and maintain complex analytics dashboards and data pipelines (e.g., Zendesk Explore, Domo, SQL) to track KPIs like ticket volume, MTTR, CSAT, and backlog trends.
- Partner with Product Analytics to build unified data reporting layers across disparate platforms.
- Perform root-cause analysis on platform trends and negative CSAT ratings to identify automation opportunities and systemic fixes.
Technical Enablement & Process Improvement
- Collaborate with Support Leadership to design and deliver technical onboarding and enablement programs for support staff.
- Digest complex product handoffs from Product and Engineering teams, translating them into technical documentation, live training modules, and internal knowledge base resources.
- Partner with Documentation and Training teams to create client-facing self-service e-learnings and articles that reduce inbound ticket volume.
- Continuously audit support workflows to identify operational bottlenecks, create documented procedures to improve them, and develop automated solutions as necessary to eliminate them.
- Maintain key relationships outside their area of expertise to bolster unified process improvement where necessary.
Requirements
Required:
- Experience: 3+ years of experience in product support engineering, support operations, technical support, or developer relations.
- Development & Scripting: Hands-on programming experience (e.g., Python, JavaScript/Node.js, REST APIs, Webhooks, JSON) to build custom tooling and integrations.
- Platform Expertise: Deep administrator/developer experience with customer support ecosystems (e.g., Zendesk API/Apps Framework, Jira Service Management, Salesforce, Freshdesk).
- Data & Analytics: Strong SQL skills and experience building dashboards in BI tools (e.g., Domo, Tableau, Looker) or native reporting engines (Zendesk Explore).
- Operations & Enablement: Proven ability to document SOPs, lead technical training, and optimize operational support workflows.
- Communication: Strong cross-functional collaboration skills to liaise effectively between Engineering, Product, and Support teams.
Preferred:
- AI & Automation Experience: Hands-on experience developing or implementing AI Agents, LLM APIs (e.g., OpenAI, Anthropic), conversational AI frameworks, or agentic frameworks (e.g., LangChain, AutoGen).
- Knowledge Management for AI: Experience with vector databases, prompt engineering, or managing knowledge bases optimized for AI search/RAG architectures.
- Best Practices: Familiarity with ITIL framework, Agile methodology, or DevOps deployment practices.
The base salary range for this full-time position is $127,500 - $191,500.