Quant Developer

Shah Equity; Hyderabad; On-site; INR 450,000 - 1,100,000; Full time

Job summary

Shah Equity is hiring a production quantitative developer to build, test, and deploy trading strategies across crypto and US equities. You will work with a PM, a Head of AI Engineering, and a quantValidation Engineer to ensure robust, automated strategy execution.

We emphasize shipping production code, live testing, and documenting strategies with full rigor. The role offers strong growth in an AI-native trading environment with equity opportunities.

Qualifications

• 2+ years of production quantitative development experience.
• Strong Python (mandatory). C++ or Rust a plus.
• Backtesting framework experience you''ve built or extensively used.
• Comfort with execution platforms IB API, Alpaca, Polygon, Binance API, or equivalent.
• Demonstrable strategy you have personally built and tested.
• Statistics fluency: Sharpe, Sortino, drawdown, walk-forward, and overfitting prevention.

Responsibilities

• Build, test, and deploy production trading strategies.
• Partner with traders to algorithmize their edge.
• Collaborate with validation engineer on stress-testing.
• Ship code that runs unattended with real money.

Skills

Python

Quant dev

C++

Rust

Backtesting

APIs

Statistics

Education

UG: Any Graduate

Tools

IB API

Alpaca API

Polygon API

Binance API

Job description

Job Description

Shah Equity is building a strategy engine designed to ship 36+ quant strategies per year across crypto and US equities. We need quantitative developers who have actually shipped systems to production not built academic backtests. The team you're joining: a PM with active trading book, a Head of AI Engineering building the agent infrastructure, a Quant Validation Engineer whose job is to break your code, and the founder who personally cares about every strategy that goes live.

Mission

Build, test, and deploy production trading strategies. Partner with traders to algorithmize their edge. Pair with the validation engineer on stress-testing. Ship code that runs unattended with real money.

90-Day Outcomes

• Ship two production strategies by Day 60
• Build or extend the backtesting framework (we already have a baseline)
• Establish documentation and code review practices the team adopts
• Successfully convert at least one manual trader's strategy into an algorithm

What You Bring

• 2+ years of production quantitative development experience
• Strong Python (mandatory). C++ or Rust a plus.
• Backtesting framework experience you've built one or extensively used one
• Comfort with execution platforms IB API, Alpaca, Polygon, Binance API, or equivalent
• Demonstrable strategy you have personally built and tested (not just modified from a tutorial)
• Statistics fluency you can talk through Sharpe, Sortino, drawdown, walk-forward, and overfitting prevention

How You'll Use AI

• Daily use of Claude or Cursor for code generation and review
• AI-assisted backtest analysis and edge case identification
• LLM-assisted documentation — every strategy you ship has full written documentation
• Partnership with Head of AI Engineering on the agent layer that orchestrates strategy execution

Compensation

4.5-11 LPA based on profile depth. Performance bonus tied to strategies you ship to production AND their actual P&L. Top performers may receive equity at the operating-entity level on strategies they own end-to-end.

Work Sample (After Initial Screen)

72 hours: build a small backtest of a simple mean-reversion strategy on data we provide. Submit GitHub repository with: code, backtest results, written analysis of the strategy's weaknesses, and your approach to preventing overfitting. We grade on code quality, statistical rigor, and the honesty of your weakness analysis (if you say the strategy is perfect, we know you didn't look hard enough).

Role Category: Trading, Asset & Wealth Management

Education

UG: Any Graduate

Key Skills

Skills highlighted with ‘‘ are preferred keyskills

Shah Equity is a multi-strategy proprietary trading firm headquartered in Dallas with engineering and trading operations in Hyderabad. We deploy capital across quantitative strategies in US equities and digital assets, with an in-house team building the agent infrastructure, validation systems, and execution layer that powers our edge.

Beyond the trading book, we operate an AI-native venture studio launching companies at high velocity using modern AI build tools, and a media operation producing high-volume content across our portfolio. The firm is privately held, founder-operated, and structured to compound.

Company Info

Address: 1412 Main St, Ste 540, Dallas, Texas 75202 , Other Turks and Caicos Islands, Turks and Caicos Islands