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):
- 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.
- 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.
- Own the operational design for lead capture, enrichment, deduplication, scoring, grading, prioritization, routing, acceptance, recycling and disqualification.
- Translate GTM policy into scalable Salesforce fields, validation rules, ownership logic, queues, automations and service-level agreements.
- Continuously improve scoring and routing using observed conversion outcomes, fit and intent signals, rep capacity and territory rules.
- Define qualification and handoff standards across Marketing, SDRs and Account Executives, with clear ownership, required context and closed-loop feedback.
- Operationalize ICP, segmentation, territory and target-account strategies into measurable account and contact universes, coverage plans and activation workflows.
- Administer and optimize Salesforce, Salesloft, Lusha, Clay, Nooks, Qualified and LinkedIn Sales Navigator, including integrations, cadences, task logic, data flows and operating standards.
- Partner with SDR leadership to define capacity, activity, quality and pipeline goals and provide analytical coaching insights by rep, channel, cadence, segment and persona.
- Ensure automated, inbound and outbound interactions enter the funnel with accurate ownership, context, qualification and attribution.
- Serve as the operational and analytical partner to Marketing, Sales Development, Sales and GTM Systems for lead-to-pipeline performance.
- Lead requirements gathering, process design, solution configuration, testing, release management, documentation, enablement and adoption measurement.
- Drive alignment on lifecycle definitions, service levels, data standards and prioritization, balancing near-term commercial needs with scalable architecture.
Analytics, Data and Decision Infrastructure:
AI, Automation and GTM Engineering:
Lead Lifecycle, Scoring and Routing:
Targeting and SDR Operating Systems:
Cross-Functional Leadership and Governance:
What You'll Need (Required Knowledge, Skills & Abilities):
- 4+ years of experience in GTM Operations, Revenue Operations, Sales Operations, Marketing Operations, GTM Engineering, Revenue Systems or an equivalent technical GTM role in a B2B technology or SaaS environment.
- Advanced analytical ability, including experience designing data models, metric definitions, dashboard architecture and scalable reporting infrastructure for operational and executive decision-making.
- Strong Salesforce proficiency across data modelling, process design, automation, reports, dashboards, permissions and data-quality governance.
- Demonstrated success building and operationalising AI-enabled workflows using low-code tools, integrations, APIs or agent-based platforms.
- Working knowledge of AI workflow design, including prompt design, structured outputs, testing and evaluation, monitoring, exception handling and human oversight.
- Hands-on experience administering or optimising a sales engagement platform such as Salesloft or Outreach.
- Experience designing lead lifecycle, scoring, routing, qualification, SDR and early-stage pipeline processes.
- Ability to combine quantitative analysis with commercial judgement, communicate clear recommendations and influence cross-functional leaders.
- Strong requirements-gathering, process-mapping, solution design, testing, documentation and change-management skills.
What Would Be Nice (Preferred Experience):
- Experience with Lusha, Clay, Nooks, Qualified and LinkedIn Sales Navigator.
- Experience with SQL, BI tools, data transformation, reverse ETL or warehouse-based reporting.
- Experience building GTM applications, internal tools or agents in a GTM Engineer capacity.
- Experience supporting enterprise account-based or target-account motions, ideally in identity verification, fraud, cybersecurity or financial services technology.
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