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JobgetherVerified from Jobgether's careers page · Lever

GTM Engineer

  • USA
  • On-site
  • 6+ Years
  • Posted Nov 11, 2026

At a glance

GTM Engineer at Jobgether, an on-site role based in USA. Experience level: 6+ Years. Posted on 11 November 2026, read from Jobgether's own careers page (Lever), which RealAnalystJobs re-checks daily and removes the role when it closes.

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About this role

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a GTM Engineer based in the United States. We are looking for a technically skilled and commercially minded GTM Engineer to strengthen and scale the technical infrastructure behind a growing go-to-market organization. Working within Revenue Operations, you will build and maintain the integrations, data pipelines, automations, and AI-powered tools that support Sales, Business Development, and Customer Success teams. You will connect critical business platforms to create reliable, unified data systems that improve visibility, efficiency, and revenue performance. You will also transform operational challenges and business requirements into scalable technical solutions using APIs, SQL, Python, and modern AI technologies. This is a hands-on engineering role focused on go-to-market systems rather than customer-facing product development. You will have significant ownership, direct exposure to leadership, and the opportunity to shape the next generation of revenue operations in a fast-growing SaaS environment. Accountabilities • Build and maintain GTM data infrastructure: Develop and manage data pipelines, data models, and identity-matching systems that integrate CRM information, product usage data, billing platforms, and external market intelligence into a unified and reliable view of customer and prospect accounts. • Develop integrations and automated workflows: Design, implement, and maintain robust integrations between platforms such as HubSpot, Maxio, Stripe, Intercom, and other business systems, replacing manual processes with scalable, automated solutions. • Manage event-driven systems: Build and maintain integrations using APIs, webhooks, and automation frameworks while implementing monitoring, error alerts, documentation, and appropriate handling of rate limits and synchronization issues. • Strengthen reporting and analytics: Develop reliable, warehouse-backed reporting infrastructure that provides accurate and timely insights into pipeline performance, sales activity, funnel conversion, sales velocity, forecasting, and multi-touch attribution. • Develop AI-powered tools and agents: Build and deploy practical AI solutions, including Claude skills, internal applications, and large language model (LLM) workflows to support prospect research, data enrichment, lead scoring, summarization, deal management, sales enablement, and customer handoffs. • Translate business signals into action: Convert customer engagement data, product usage signals, prospecting triggers, account intent, and enrichment information into automated prioritization, routing, and actionable tasks for Sales and Customer Success teams. • Improve GTM productivity: Identify opportunities to eliminate repetitive work, streamline operational processes, and equip commercial teams with reliable tools that improve efficiency and execution. • Measure system performance and business impact: Track adoption, data quality, time saved, pipeline influence, and overall effectiveness of the systems and tools developed. Continuously optimize successful solutions and discontinue those that do not deliver measurable value. • Collaborate with Revenue Operations: Work closely with RevOps leadership and stakeholders to translate strategic priorities and business requirements into technically sound systems, while supporting governance, standardization, and cross-functional alignment. • Ensure technical reliability and documentation: Take end-to-end ownership of technical solutions, maintain clear architectural documentation, implement monitoring systems, and proactively address issues to ensure reliable operations. Requirements • 3–6+ years of professional experience in Revenue Operations, Sales Operations, or other technical go-to-market roles. • Strong understanding of commercial operations, including sales pipeline management, funnel conversion, sales quotas, forecasting models, and attribution methodologies. • Advanced, hands-on experience with HubSpot, including custom objects, properties, complex workflows, system architecture, and API integrations. • Strong SQL skills, including querying, data manipulation, and transformation, combined with practical Python experience or proficiency in an equivalent scripting language. • Demonstrated experience working with REST APIs, webhooks, data integrations, and automated data pipelines. • Practical experience building and deploying AI-powered workflows using Claude or other large language models, with examples of solutions that remain actively used and deliver ongoing business value. • Familiarity with AI-assisted coding tools and the ability to incorporate them into daily development workflows to improve speed and productivity. • Strong systems architecture and problem-solving capabilities, with the ability to transform ambiguous business requests into scalable technical solutions and efficient operational processes. • Ability to communicate complex technical concepts and architectural trade-offs clearly to non-technical stakeholders, particularly commercial and revenue leadership teams. • Excellent documentation, monitoring, and quality assurance practices, with a strong sense of ownership over system reliability and business outcomes. • A proactive, independent, and results-oriented mindset, with the ability to manage priorities and deliver solutions without relying exclusively on predefined technical specifications. Additional Assets: • Experience working with subscription billing and recurring revenue data through platforms such as Stripe or Maxio. • Familiarity with modern data warehouse technologies, including Snowflake and BigQuery, as well as dbt for data transformation. • Experience with workflow automation and orchestration platforms such as n8n, Clay, or Temporal. • Previous experience in multi-product SaaS environments or organizati

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