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Co Founder & Cto Panipat (India)

Important Business·Posted 1 week ago

Location

Panipat, Haryana, IN

About the Role

Co-Founder (CTO) | AI-Driven GTM Platform

We’re building a no-code GTM-AI platform where AI agents autonomously run go-to-market workflows—where you can find your user in your website research, personalization, orchestration, and continuous learning.

The GTM world is moving from disconnected tools to AI-led execution systems , and we already have paying customers validating this shift.

P.S -This is a co-founder role for someone who plans to build long-term and is willing to invest capital as part of that commitment. If this aligns with how you like to build and invest, please apply.

Where We Are

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Live product with production GTM workflows
~$1,500 USD MRR and growing
Strong GTM, growth, and customer access from the founding team
Clear technical direction with room to shape the architecture

What We’re Building

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Agentic AI workflows for real GTM teams
LLM-driven personalization and decisioning
Learning loops based on outcomes, not dashboards
Straightforward UX over complex intelligence

Who This Is For

This is a true co-founder role for someone who:

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Has built AI workflows or agentic systems before
Is hands-on with LLMs, orchestration, tools, memory, RAG, and evaluation
Thinks in terms of ownership, not employment
Believes that shared risk builds shared conviction
Is comfortable aligning early through both effort and capital to move faster and build right

What You’ll Own

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End-to-end technical and AI architecture
Designing, shipping, and scaling agent systems
Turning resources into execution velocity
Co-leading product, strategy, and long-term direction
Building the foundation for a robust engineering org

This Is / Is Not

This is:

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A high-ownership, high-trust co-founder journey
Early stage, rapid learning, real impact
A role where commitment matters more than titles

This is NOT: .
A salaried CTO role
A passive or low-involvement opportunity
A comfort-first, playbook-driven job

If you’re excited by 0 → 1 building , shared upside, and meaningful ownership—let’s talk.

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Ideal Candidate

Someone who has shipped AI agent systems or LLM orchestration in production (not just POCs), has hands-on depth in RAG/memory/evaluation, and has previously made founder-level decisions about architecture trade-offs under uncertainty.

Likely Interview Questions

1.Walk us through a time you designed an agentic system end-to-end—what was the learning loop, how did you evaluate agent performance, and what broke?
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🔒 Strengths to highlight + red flags locked.

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