AI Workflow Specialist (GTM)
ABOUT THIS PROFILE This role owns the full AI-powered go-to-market pipeline — from sourcing and qualifying leads through to outreach, pipeline management, and renewal risk detection. The engineer works upstream (data acquisition, ICP matching, database building) and downstream (outreach sequencing, CRM automation, churn prediction) to compound revenue growth and reduce manual overhead across Sales, Marketing, and Account Management. WHY THIS PROFILE MATTERS GTM is where revenue is made or lost. This role goes beyond just automating outreach — it starts with building the qualified lead database in-house, replacing external agencies with scalable AI-driven sourcing. Every week of delay is lost pipeline velocity. KEY RESPONSIBILITIES Data Acquisition & Qualification Framework: Research and aggregate data sources across target markets, including licensing registries, government databases, and third-party data providers. Build a custom qualification framework to identify and verify target accounts. ICP Definition & Lead Database Building: Define Ideal Customer Profiles based on industry, company size, region, and decision-maker roles. Build and maintain an enriched, verified database of qualified accounts and contacts, segmented by priority market. Data Extraction & Enrichment: Extract data from official registries and public sources, enrich and segment accounts, research additional contacts on LinkedIn, and deliver verified databases aligned with the ICP. AI SDR Outreach Sequencing: Design and deploy AI-driven outbound sequences that personalise messaging at scale, A/B test approaches, and auto-enrich prospect data from CRM and third-party sources. Lead Scoring & Routing: Build and maintain models that score inbound and sourced leads against ICPs, integrating with CRM workflows to route high-intent leads in real time. Churn & Renewal Risk Scoring: Develop predictive models that flag at-risk accounts 60–90 days before renewal, feeding proactive intervention workflows for Account Management. Marketing Content Generation: Build automated pipelines for generating, reviewing, and publishing marketing content using LLM-based workflows. Competitive Intelligence Monitoring: Set up automated systems that track competitor activity, pricing changes, and product launches. Pipeline Hygiene & CRM Automation: Automate data entry, deal stage progression, activity logging, and reporting. Integrate qualified lead data directly into CRM systems and ongoing lead generation workflows. Outbound Campaign Execution: Move beyond database building into executing AI-powered outbound marketing campaigns, including cold outreach, nurture sequences, and geographic expansion strategies. REQUIRED SKILLS Python with LLM orchestration frameworks (LangChain, LlamaIndex, or equivalent) CRM platforms (Salesforce, HubSpot) and their APIs, including data import/sync Web scraping, data extraction, and enrichment tools (Apollo, Clay, Clearbit, LinkedIn Sales Navigator) Workflow automation tools (n8n, Zapier, Make) and production integrations Prompt engineering for reliable, production-grade LLM workflows Database design for lead management and segmentation GTM metrics (MQL/SQL conversion, pipeline velocity, churn rate, NRR) Nice to Have Background in revenue operations, sales engineering, or growth engineering Experience building custom data acquisition frameworks from public registries ABM (Account-Based Marketing) strategies and tooling Vector databases for semantic search and recommendation