Eventual in plain talk: building Daft, an open‑source engine that makes AI data as easy to wrangle as spreadsheets. Already powering stuff at Amazon and Tesla, backed by the Databricks crowd.
Looking for a GTM automation nerd: part‑time, 3‑6 months, 4 days in our SF Mission spot. You'll be the bridge between code and customers.
Daily beat: teach AI tools to find prospects, dig through tech blogs for signals, keep HubSpot humming, and turn open‑source users into paying ones.
Who fits: someone who's automated their way out of boring jobs before, writes decent code, and gets equally fired up about clean APIs and closed deals.
Perks are startup‑classic: office meals, poker nights, new Apple gear—but the real draw is helping build the plumbing for tomorrow's AI.
About Eventual
Every breakthrough AI application, from foundation models to autonomous vehicles, relies on processing massive volumes of images, video, and complex data. But today’s data platforms (like Databricks and Snowflake) are built on top of tools made for spreadsheet-like analytics, not the petabytes of multimodal data that power AI. As a result, teams waste months on brittle infrastructure instead of conducting research and building their core product.
Eventual was founded in 2022 to solve this. Our mission is to make querying any kind of data, images, video, audio, text, as intuitive as working with tables, and powerful enough to scale to production workloads. Our open-source engine, Daft, is purpose-built for real-world AI systems: coordinating with external APIs, managing GPU clusters, and handling failures that traditional engines can’t. Daft already powers critical workloads at companies like Amazon, Mobileye, Together AI, and CloudKitchens.
We’ve assembled a world-class team from Databricks, AWS, Nvidia, Pinecone, GitHub Copilot, Tesla, and more, quadrupling our size within a year. With Series A and seed funding from Felicis, CRV, Microsoft M12, Citi, Essence, Y Combinator, Caffeinated Capital, Array.vc, and top angels from the co-founders of Databricks and Perplexity, we’re looking to double the team now. Join us—Eventual is just getting started.
Please note we're looking for individuals who are excited to be a part of a tight-knit team working together 4 days / week in our SF Mission district office. We expect the internship to be part-time for 3 - 6 months.
Your Role:
As our GTM Engineer intern, you'll be the technical architect of our go-to-market discovery and automation engine. Working directly with our Head of Ops, you'll use AI tools and data analysis to automate outreach to our ICP, build the systems that scale our customer research, and drive efficient use of our CRM. This is a unique opportunity to shape a startup's GTM strategy from the ground up while developing cutting-edge skills in revenue automation and customer intelligence.
Key Responsibilities:
Customer Discovery: Use AI tools (Clay, Claude Code, n8n, Zapier, etc) to build lists of target ICPs, monitor intent signals, personalize outreach, and automate outboundCustomer Intelligence: Do deep dives into technical blogs, financial statements, etc to build profiles of targeted ICPs ahead of meetingsRevenue Operations: Automate collection and maintenance of HubSpot data, build automated workflows for lead routing and follow-up, create dashboards and reporting systemsProduct-Led Growth: Leverage data about existing open-source users to drive personalized outreach and campaigns
What we look for:
Automation obsessed - you get excited about building workflows that eliminate repetitive work and have automated away tedious tasks in the pastScrappy builder - you've hustled hard in your previous roles and achieved successful outcomes through experimentationSystems thinker - you see and track the big picture of how data flows from outreach to closed customer and can pinpoint areas of improvement using dataCommercial + technical hybrid - you care as much about driving revenue as you do about clean code/data; you can talk ROI with leadership and API integrations with engineersComputer science or business background preferred - whether you learned to code in school or picked up technical skills building side projects, you have the baseline to work with APIs, databases, and automation tools; new grads are welcome to apply
Perks & Benefits
In-person tight knit team with 4x a week in officeCatered lunches and dinners for SF employeesTeam building events & poker nightsFlexible PTOLatest Apple equipment
Eventual
Software Development
11-50 employees
Series A • 33M
6-month: %
12-month: %