Profound
GTM Engineer, Post-Sales
About this role
Profound seeks a GTM Engineer for their Post-Sales team to build data-driven infrastructure that automates customer retention and expansion workflows. You'll create intelligent systems like health scoring, expansion detection, and renewal risk alerts that empower Customer Success teams to operate at scale.
What you'll do
- Build automated customer health scoring by synthesizing product usage, support signals, and engagement data
- Design expansion signal detection to identify accounts ready for upsells based on usage patterns and activity
- Automate recurring customer lifecycle touchpoints including onboarding checklists and adoption nudges
- Create renewal risk scoring to flag at-risk accounts 60+ days before renewal
- Generate business review materials by aggregating usage metrics and ROI data from internal sources
- Analyze call recordings to identify AI use cases and automate deployment at scale
What they're looking for
- Python or JavaScript programming
- Data pipeline development and API integration
- AI and LLM APIs with agentic automation
- Salesforce, Gong, n8n, or similar platform experience
- Statistical modeling and predictive signal detection
- Post-sales or customer success operations knowledge
- Systems thinking across customer lifecycle data flows
- High-agency product building with minimal oversight
Benefits
- Base salary $130,000–$200,000
- Equity compensation
- Competitive benefits and perks package
- On-site role in Union Square, NYC office
- Work on AI-native products at the frontier of marketing technology
- Fast-moving, lean team with global offices
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Profound
Profound builds an AI-native marketing platform used by Fortune 500 companies that automates lead qualification, scoring, and routing while capturing prospect intent signals. The company is hiring Infrastructure Engineers, Data Engineers, Design Engineers, GTM Engineers, and Talent Engineers to scale its cloud systems, data pipelines, user experiences, and internal recruiting automation.
View all jobs at ProfoundLikely interview questions
- Walk us through a time you built an automated workflow or data pipeline that directly improved how a team operated. What was the problem, and how did you measure success?
- How would you approach building a customer health score from scratch? What data sources would you prioritize, and how would you validate that your score actually predicts churn or expansion?