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.

• 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.

Targeting and SDR Operating Systems:

• Operationalize ICP, segmentation, territory and target‑account strategies into measurable account and contact universes, coverage plans and activation workflows.

• Administer and optimise 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.

Cross‑Functional Leadership and Governance:

• 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 prioritisation, balancing near‑term commercial needs with scalable architecture.

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.