Build, configure, test, and optimize AI agents that support Marketing and SDR workflows across prospecting, enrichment, scoring, routing, outreach, and reporting Develop agentic workflows using tools such as Claude, Clay, MCP, Snowflake, Salesforce, HubSpot, Outreach, Gong, and related GTM systems Translate business requirements into structured AI workflows that can operate reliably, repeatably, and at scale Build agents that monitor key GTM signals such as job changes, hiring velocity, funding events, web intent, content engagement, and account fit Create workflows that reduce manual research and give SDRs better prioritized accounts, stronger contact context, and cleaner outreach hooks Help build and scale autonomous prospecting motions that identify ICP-fit accounts and contacts based on real-time buying signals Support ICP fitness scoring workflows that assess inbound leads, event leads, partner leads, and prospecting lists before they move into downstream systems Build logic that blends signal-based prospecting with broader whitespace nurture motions Develop workflows that help SDRs prioritize the right accounts at the right time with the right message Partner with Marketing, SDR, and RevOps teams to ensure AI-driven prospecting aligns with pipeline goals, territory strategy, and campaign priorities Connect and normalize data across Salesforce, HubSpot, Clay, Snowflake, Outreach, Gong, LinkedIn Ads, HockeyStack, and other GTM platforms Build structured inputs, data models, prompts, API workflows, and JSON-based logic that allow AI agents to take action with clean context Support audience segmentation workflows across cold, warm, and hot account/contact cohorts Help operationalize Snowflake and other data sources as audience and intelligence layers for AI-powered GTM activation Partner with Marketing Operations, RevOps, Data, and IT teams to make sure agent workflows are secure, governed, and aligned with system architecture Build and maintain AI-powered data quality workflows that improve the accuracy of CRM and marketing data Support agents for employment verification, LinkedIn URL enrichment, region/location detection, account/contact enrichment, and stale data detection Design workflows that catch bad records before SDRs waste time on outdated contacts or inaccurate account information Improve the quality of downstream workflows by ensuring agent decisions are based on clean, current, and complete data Partner with Salesforce and HubSpot system owners to write back useful intelligence in a structured and governed way Build workflows that support AI-generated email sequences, personalized outreach hooks, account research summaries, and meeting preparation briefs Help connect outbound email, LinkedIn Ads, website intent, events, and partner motions into a more unified activation model Support agent workflows for event and user group planning, including geographic intelligence based on pipeline, whitespace, and ICP contact density Partner with SDR leadership to improve rep efficiency, reduce manual research, and increase time spent on high-value conversations Help create feedback loops that improve messaging, scoring, segmentation, and workflow performance over time Test agent outputs for accuracy, consistency, brand alignment, and business usefulness Build repeatable QA processes for prompts, structured inputs, workflow logic, and agent-generated outputs Identify where human review is required versus where automation can safely run independently Monitor workflow performance and recommend improvements based on adoption, output quality, conversion impact, and operational efficiency Partner with Security, IT, and Operations teams to ensure AI workflows follow internal governance and data handling standards