Founding GTM Engineer at RamAIn

RamAIn builds the world’s fastest computer-use agents for enterprise work. We’re a YC W26 company on a mission to eliminate repetitive, manual workflows by training AI agents that operate legacy systems, desktop apps, and web portals the same way humans do — but 10× faster and more reliably.

Founders

RamAIn was founded by Shourya Vir Jain (CEO) and Vansh Ramani (CTO), who met at IIT Delhi and dropped out to build AI-native automation for enterprise workflows.

Shourya previously worked at McKinsey, where he saw firsthand how much enterprise work still depends on manual interaction with legacy systems. He is also a FIDE-rated chess player (2118), was ranked top-20 globally under 16, and previously built and scaled an enterprise AI company to over 6-figures in ARR.

Vansh is an AI researcher who worked at CMU on scalable machine learning and representation learning. His research includes publications at ICLR and ACS, and “Panaroma,” one of the fastest vector search algorithms, later merged into Meta’s FAISS. He focuses on building high-performance reasoning and planning systems for real-world deployment.

Role

We’re looking for a technical GTM builder to own our top-of-funnel revenue infrastructure as our first business hire. You’d be the third person working full-time on the company, working directly with the founders.

This is a good fit if you’ve built outbound systems from scratch – wiring together enrichment pipelines, AI personalization, and sequencing automation – and you want to apply that to one of the most interesting problem spaces in enterprise AI.

What you’ll own

• Designing and owning our outbound infrastructure end-to-end: lead enrichment, ICP scoring, AI-personalized sequences, and email deliverability
• Building automations that surface buying signals and trigger the right outreach at the right time
• Owning CRM architecture – workflows, reporting, and pipeline visibility
• Experimenting with new channels and approaches to generate qualified pipeline
• Identifying where manual GTM work can be automated and building the system to replace it

What we’re looking for

• 0–4 years of experience in GTM engineering, technical RevOps, or a growth/marketing role where you were building automations and pipelines, not just running campaigns
• Hands-on with modern GTM tooling – Clay, Apollo, Instantly, or similar – you’ve built multi-step enrichment and sequencing workflows, not just set up a table
• Comfortable with Python or SQL well enough to work with data, call APIs, and build lightweight scoring or enrichment logic
• Top-of-funnel focused – you know how to build systems that generate qualified pipeline at scale, from ICP definition through to booked meetings
• Genuine interest in AI; ideally you’ve used LLMs to automate research, personalization, or signal detection in a GTM context