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# Algorithmic Trading Developer

- **Company:** Homex Corporation
- **Location:** United States (Remote available)
- **Contract:** Internship / Graduate position
- **Skills:** Application Programming Interfaces (APIs), Algorithmic Trading, Data Retrieval, Github, Python (Programming Language), NumPy, Backtesting, SQL Databases, Data Logging, Data Ingestion, Pandas, Docker
- **Published:** June 9, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=c2e5bc2354f4c497

## About the Role

Do you have experience in Trading risk assessments?, Strong Python programming experience

Proven experience with Interactive Brokers API / ib_insync / TWS API / IB Gateway

Experience building and deploying algorithmic trading systems

Experience with backtesting frameworks such as:

Backtrader
Zipline
vectorbt
QuantConnect
custom pandas-based backtesting

Strong knowledge of trading concepts:

candlesticks
support/resistance
zigzag / swing highs and lows
ATR
volume
order types
slippage
commissions
risk management

Experience with pandas, NumPy, SQL, APIs, and logging

Ability to write clean, modular, well-documented code

Preferred Skills

Experience with options, futures, equities, or ETFs

Experience deploying strategies on cloud/VPS

Experience with GitHub, Docker, scheduling jobs, and monitoring

Experience converting Thinkorswim / ThinkScript logic into Python

Experience with mean reversion, breakout, trend-following, or reversal strategies

## Description

I am looking to hire an experienced algorithmic trading developer to build, backtest, and deploy trading strategies using Interactive Brokers / IBKR API.

The developer must have hands-on experience with IBKR Trader Workstation or IB Gateway, live market data, order execution, historical data retrieval, backtesting, and risk-controlled live deployment.

Responsibilities

Build Python-based trading infrastructure using the Interactive Brokers API

Connect to IB Gateway / TWS API for:

historical data
real-time market data
order placement
position tracking
trade monitoring
account status
error handling and reconnect logic

Develop and backtest trading strategies using historical intraday and daily data

Convert strategy logic into live executable code

Create modular code for:

data ingestion
indicator calculations
signal generation
position sizing
risk management
order execution
logging and reporting

Build paper-trading deployment first, then support live deployment

Add safety controls such as max loss, max position size, duplicate order prevention, stop-loss logic, and kill switch

Provide clean documentation and handoff instructions


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