Sr. GTM Knowledge Engineer
At ZoomInfo, we power business growth through the world’s most comprehensive Go-to-Market Intelligence Platform. With 1,800+ sellers and customer-facing teams engaging prospects and customers every day, instant access to trusted knowledge, learning, and answers is mission-critical.
As our Sr. GTM Knowledge Engineer, you will design and build the technical infrastructure that enables knowledge delivery across our GTM ecosystem. Sitting at the intersection of Revenue Enablement and Engineering, you will integrate platforms, automate workflows, and develop solutions that enhance search, retrieval, and content delivery, including AI-powered capabilities.
You’ll partner with AI engineers and cross-functional stakeholders to ensure systems are connected, data is reliable, and knowledge is accessible at the moment of need. This role is ideal for someone who enjoys building, debugging, and improving technical systems while enabling real business impact.
What You'll Do:
Technical Development & Implementation (50%)
- Build and maintain integrations between learning platforms, content management systems, and enablement tools using APIs with webhooks, and modern data tooling (Fivetran, Hightouch).
- Develop front-end interfaces and back-end workflows for content delivery and knowledge retrieval using React, JavaScript, and TypeScript.
- Write scripts (Python, JavaScript, or similar) that integrate with LLMs to automate content workflows and data processes
- Implement AI-powered features for search, tagging, and content recommendations, with experience using AI coding assistants, i.e. Cline, Cursor, Claude Code
- Build and maintain database schemas, queries, and data models for knowledge systems, with experience with Snowflake (preferable but not required to have exposure to dbt modeling and Airflow-based orchestration).
- Develop custom solutions to enhance platform functionality and user experience
Information Ecosystem Audits & QA (35%)
- Facilitate regular audits of content accuracy, versioning, and metadata quality across all platforms
- Conduct QA testing on integrations, workflows, and automated processes
- Monitor data integrity and identify gaps or inconsistencies in knowledge repositories
- Test and validate AI-enhanced search and retrieval functionality
- Document technical issues and coordinate resolution with appropriate teams
- Establish and maintain QA protocols for content governance and system health
System Maintenance & Optimization (15%)
- Monitor performance of integrations and automated workflows, preferably using Datadog, Montecarlo, or Pager Duty
- Troubleshoot technical issues and implement fixes
- Maintain documentation for technical implementations and processes
- Support testing and rollout of new technical features
- Track system analytics and identify optimization opportunities
Working Relationships & Collaboration Model
This role operates at the intersection of Revenue Enablement strategy and technical execution:
Primary Accountability: Revenue Enablement - Learning Experience & Technology team
- Receives strategic direction and priorities from Revenue Enablement leadership
- Translates enablement requirements into technical specifications
- Ensures solutions align with revenue team needs and learning objectives
Key Technical Partnership: Enterprise AI Engineering & Technology Teams
- Partners closely with Enterprise AI's expert engineers and technologists for technical implementation
- Collaborates on architecture, integration patterns, and best practices
- Serves as the enablement liaison to technical teams, bridging business requirements with technical solutions
- Participates in technical planning and sprint activities with engineering partners
Collaboration Style:
- Acts as a technical translator between enablement stakeholders and engineering teams
- Implements solutions based on strategic direction while leveraging engineering expertise
- Maintains strong working relationships across both business and technical functions
- Comfortable working in a collaborative, cross-functional environment
What You Bring:
Must-Have Prerequisites
Education: Bachelor's degree in Computer Science, Information Systems, Software Engineering, or related technical field (or equivalent practical experience)
Experience: 2-5+ years in a technical development role with hands-on coding experience
Technical Skills (Required):
- Front-end development: HTML, CSS, JavaScript (React, Vue, or similar framework experience a plus)
- Back-end development: Python, Node.js, or similar server-side language
- API development and integration: RESTful APIs, webhooks, authentication protocols
- Database skills: SQL, data modeling, query optimization
- Version control: Git/GitHub
- Scripting and automation: Python, JavaScript, or Bash
- Data structures and algorithms: Strong foundational knowledge
Platform Experience:
- Experience integrating with third-party platforms via APIs
- Familiarity with workflow automation tools (Zapier, Make, n8n, or similar)
- Basic understanding of enterprise software systems
Preferred Qualifications
- Experience working with CMS, LMS, or CRM systems (Salesforce, HubSpot, WordPress, Contentful, Moodle, Canvas, etc.)
- Experience with AI/ML APIs (OpenAI, Anthropic, or enterprise AI platforms)
- Familiarity with enablement or learning platforms (Allego, Seismic, Highspot, etc.)
- Experience with content databases (Notion API, Airtable, Google Drive API)
- Knowledge of search technologies (Elasticsearch, Algolia, vector databases)
- Background in SaaS or B2B technology companies
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