Founding AI Engineer / Product Builder (Help Shape an AI Analytics Platform)
Budget: ₹12,500 – ₹37,500 INR
We're building DataHorizon (https://datahorizon.ai/) —an AI copilot for Google Analytics 4 that helps marketers understand their data through natural language instead of complex dashboards.
The platform is live and functional. Now we're looking for exceptional engineers and product thinkers who enjoy taking products from good to remarkable.
This isn't a "build me a website" project.
It's an opportunity to influence product direction, experiment with AI workflows, and help shape features that thousands of marketers may eventually use.
What You'll Work On
Instead of following a rigid task list, you'll be expected to think like a product owner.
You'll explore the platform, identify friction points, propose improvements, build prototypes, and validate ideas before implementation.
Frontend Experience
Help us build an interface that feels closer to Cursor or Notion than a traditional analytics dashboard.
Potential areas include:
Faster dashboards
Interactive AI conversations
Timeline-based insights
Real-time anomaly notifications
Personalized workspaces
Better onboarding
Improved data visualizations
AI-generated reports
Mobile responsiveness
Delightful micro-interactions
We're looking for ideas—not just implementation.
Backend Engineering
Improve the foundation.
Possible work includes:
API optimization
Database performance
Better caching
Background job architecture
Queue optimization
Authentication improvements
Security hardening
Scalable service architecture
Test coverage
Monitoring & observability
The objective is a backend that's easier to maintain as usage grows.
AI & Intelligence Layer
This is where we'd love your creativity.
Help improve how the platform reasons about analytics.
Possible areas include:
Better anomaly detection
Smarter recommendations
Improved prompt engineering
Retrieval-Augmented Generation (RAG)
Context-aware insights
Conversation memory
Feature engineering
Model evaluation
Explainability
Hallucination reduction
We're less interested in swapping models and more interested in producing insights users actually trust.
What Success Looks Like
By the end of the engagement, we'd like to see:
A noticeably faster and more polished product
At least one feature that users genuinely love
Cleaner architecture
Better AI output quality
Clear technical documentation
Reproducible experiments
Production-ready code
Ideal Candidate
You're likely a strong fit if you have experience with:
React / Next.js
TypeScript
Node.js
Python
AI products
LLM integrations
Vector databases
PostgreSQL
Cloud infrastructure
Product thinking
UX intuition
Bonus if you've built analytics or marketing technology.
Before You Apply
Please answer these questions:
What's the most impressive AI product you've built?
If you had one week to improve DataHorizon, what would you build first?
Share one SaaS product whose UX you admire and explain why.
What's the biggest mistake you see AI SaaS products making today?
Include links to products you've shipped—not just GitHub repositories.
What We're Really Looking For
We don't need someone who simply completes tickets.
We're looking for someone who enjoys questioning assumptions, proposing better ideas, and helping build a product users genuinely love.
If that sounds like you, we'd love to hear from you.
The platform is live and functional. Now we're looking for exceptional engineers and product thinkers who enjoy taking products from good to remarkable.
This isn't a "build me a website" project.
It's an opportunity to influence product direction, experiment with AI workflows, and help shape features that thousands of marketers may eventually use.
What You'll Work On
Instead of following a rigid task list, you'll be expected to think like a product owner.
You'll explore the platform, identify friction points, propose improvements, build prototypes, and validate ideas before implementation.
Frontend Experience
Help us build an interface that feels closer to Cursor or Notion than a traditional analytics dashboard.
Potential areas include:
Faster dashboards
Interactive AI conversations
Timeline-based insights
Real-time anomaly notifications
Personalized workspaces
Better onboarding
Improved data visualizations
AI-generated reports
Mobile responsiveness
Delightful micro-interactions
We're looking for ideas—not just implementation.
Backend Engineering
Improve the foundation.
Possible work includes:
API optimization
Database performance
Better caching
Background job architecture
Queue optimization
Authentication improvements
Security hardening
Scalable service architecture
Test coverage
Monitoring & observability
The objective is a backend that's easier to maintain as usage grows.
AI & Intelligence Layer
This is where we'd love your creativity.
Help improve how the platform reasons about analytics.
Possible areas include:
Better anomaly detection
Smarter recommendations
Improved prompt engineering
Retrieval-Augmented Generation (RAG)
Context-aware insights
Conversation memory
Feature engineering
Model evaluation
Explainability
Hallucination reduction
We're less interested in swapping models and more interested in producing insights users actually trust.
What Success Looks Like
By the end of the engagement, we'd like to see:
A noticeably faster and more polished product
At least one feature that users genuinely love
Cleaner architecture
Better AI output quality
Clear technical documentation
Reproducible experiments
Production-ready code
Ideal Candidate
You're likely a strong fit if you have experience with:
React / Next.js
TypeScript
Node.js
Python
AI products
LLM integrations
Vector databases
PostgreSQL
Cloud infrastructure
Product thinking
UX intuition
Bonus if you've built analytics or marketing technology.
Before You Apply
Please answer these questions:
What's the most impressive AI product you've built?
If you had one week to improve DataHorizon, what would you build first?
Share one SaaS product whose UX you admire and explain why.
What's the biggest mistake you see AI SaaS products making today?
Include links to products you've shipped—not just GitHub repositories.
What We're Really Looking For
We don't need someone who simply completes tickets.
We're looking for someone who enjoys questioning assumptions, proposing better ideas, and helping build a product users genuinely love.
If that sounds like you, we'd love to hear from you.