GTM Engineer, Post-Sales

Profound · New York, New York$10,833–$16,667 USD/mesmid

En corto

▸Construyes sistemas automáticos para retener y expandir clientes usando datos de producto, soporte y uso.
▸Automatizas flujos de trabajo clave: salud de clientes, renovaciones, expansión y presentaciones de negocios.
▸Trabajas con IA, agentes y APIs para escalar la experiencia de cliente sin necesidad de intervención humana constante.

Comfortable reasoning about data at a statistical level; building signal detection and pre

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¿Qué piden?

✓Experiencia en operaciones de post-venta, customer success o account management
✓Fluidez técnica en Python o JavaScript
✓Capacidad para construir y gestionar pipelines de datos
✓Experiencia con herramientas como Gong, Salesforce, n8n, Gainsight o Dust
✓Capacidad para razonar estadísticamente y construir señales predictivas
✓Mindset de builder con autonomía para definir y entregar soluciones

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PythonJavaScriptGongSalesforcen8nGainsightDustLLM APIsAPI integrationsData pipelines

¿A quién escribirle en Profound?

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Compensation: $130K – $200K • Offers Equity. Profound is the marketing platform for the age of AI search. The way brands reach people is being rewritten — AI models like ChatGPT, Perplexity, and Google AI Mode are now the answer layer between companies and their customers. We built the platform marketers use to understand, measure, and win in that world: the analytics, intelligence, and agent automation that turn AI search from a threat into a competitive advantage. We went from 0 to a $1B valuation in 18 months. Revenue grew 100x last year. Our customers include 15% of the Fortune 500 like Walmart, Wayfair and U.S. Bank, and innovators like Ramp, MongoDB, and Figma. We are backed by Sequoia, Kleiner Perkins, LSVP, and Khosla Ventures — and we are moving fast enough that the people joining now are building the playbook everyone who comes after them will run. As a GTM Engineer on the Post-Sales team, you will build the infrastructure that powers how we retain and grow our customer base. Part systems architect and part customer intelligence platform, you will turn data from across the customer lifecycle into automated workflows that give engagement managers and account managers real leverage. Your work will directly shape how our Customer Success function scales. WHAT YOU’LL DO - Build automated customer health scoring across the full book of business, synthesizing product usage, support signals, and engagement data into a single, reliable picture of each account - Design expansion signal detection for account managers that automatically surfaces accounts ready to grow, flagging patterns in usage, seat activity, and engagement that typically precede an upsell conversation - Automate recurring touchpoints across the customer lifecycle, including onboarding checklists, usage review summaries, and adoption nudges, so engagement managers can focus on the work that requires a human - Build renewal risk scoring that surfaces at-risk accounts 60 or more days before their renewal date, giving the team the time and context to intervene effectively - Generate business review materials automatically by pulling usage metrics, ROI data, and AI use case recommendations from multiple internal sources into a format teams can present immediately - Analyze call recordings and transcripts to identify AI use cases that map to each customer’s business, then automate the process of building and deploying those use cases at scale - Build routing logic for assigning new customers to the right team member at handoff, accounting for current workload, open renewals, domain expertise, and timezone alignment - Manufacture tools rather than operate them, building systems the post-sales team can run independently WHO YOU ARE - High-agency builder who can identify a problem in the customer lifecycle, scope a solution, and ship it without being closely managed - Technically fluent in Python or JavaScript, comfortable building data pipelines, integrating APIs, and working across tools like Gong, Salesforce, and n8n - AI-native thinker who defaults to automation and regularly experiments with agents, LLM APIs, and workflow frameworks - Pragmatic about build versus buy, knowing when to leverage existing infrastructure rather than rebuild it - Experience with post-sales, customer success, or account management operations - Comfortable reasoning about data at a statistical level; building signal detection and predictive models, not just moving records between systems - Familiar with tools like Gainsight, Gong, Salesforce, Dust, or similar customer-facing platforms - Systems thinker who sees how data moves through the customer lifecycle and builds with that full picture in mind - Comfortable operating in ambiguity and structuring your own roadmap LOCATION This is an on-site role based in our Union Square, NYC office, designed for builders who thrive on speed, iteration, and meaningful impact. For this role, the expect

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