GTM Engineer

We are seeking a highly analytical, technically proficient GTM Engineer to own the data, AI workflows, systems and operating processes that move demand from targeting and lead creation through qualified early-stage pipeline. This is a hands-on builder role at the intersection of GTM Operations, analytics and GTM Engineering. The successful candidate will establish trusted reporting infrastructure, turn funnel data into decisions, and build governed AI-enabled workflows that materially improve lead quality, conversion, speed and SDR productivity.

What You'll Do (Key Responsibilities):

Analytics, Data and Decision Infrastructure:

• Own the analytical foundation for the lead-to-opportunity funnel, including the data model, metric definitions, source-of-truth logic, transformations and dashboard architecture.
• Build reliable reporting for volume, conversion, velocity, acceptance, aging, leakage, pipeline value and target-account penetration across source, campaign, segment, persona, account tier, channel and owner.
• Evaluate lead-scoring efficacy, routing performance, outreach productivity and handoff quality using cohort, trend and root-cause analysis; translate findings into prioritized actions.
• Create data-quality monitoring, reconciliation and reporting QA so leaders can trust funnel insights and understand metric lineage.
• Develop recurring early-pipeline outlooks and decision-ready performance narratives that clearly identify risks, opportunities and recommended interventions.

AI, Automation and GTM Engineering:

• Design, build and operate production-ready AI workflows for account and contact research, enrichment, prioritization, personalization, qualification, routing QA, SDR preparation, next-best action and performance diagnosis.
• Connect AI capabilities to GTM systems and structured data using low-code tools, integrations, APIs and agent-based platforms; design for repeatability rather than one-off experimentation.
• Define prompts, structured outputs, evaluation criteria, exception handling, human-in-the-loop controls and monitoring for accuracy, adoption and business impact.
• Apply appropriate governance for data security, permissions, transparency and responsible use while continuously testing and improving workflow performance.
• Identify high-value automation opportunities, quantify expected benefit and measure realized gains in conversion, speed, quality and team capacity.

Lead Lifecycle, Scoring and Routing:

• Own the operational design for lead capture, enrichment, deduplication, scoring, grading, prioritization, routing, acceptance, recycling and disqualification.