Quant Developer / AI Research Engineer

About Shah Investors & Role

Shah Investors Home Ltd. is a SEBI-registered broking firm operating since 1994, known for its trust, integrity and long-standing presence in financial markets.

We welcome highly skilled and ambitious individuals who are passionate about their work and interested in contributing to a research-driven environment across quantitative research, trading systems, data science and financial modelling.

Currently We are looking for a highly analytical and technically strong Quant Developer / AI Research Engineer to work closely with quantitative analysts and traders in building research tools, trading infrastructure and strategy testing frameworks.

The role involves working with large financial datasets, developing robust back testing and analytics systems and rapidly prototyping ideas that can be transformed into testable and production-ready trading logic. You will support research and strategy development across Indian and U.S. markets.

This role also requires familiarity with modern AI workflows, including Large Language Models (LLMs) and agentic AI systems, to support research automation, coding, experimentation and workflow orchestration.

Key Responsibilities :

• Collaborate with quantitative analysts and researchers on trading ideas and simulations.
• Build and maintain back testing frameworks and research tools.
• Process and analyse large-scale financial datasets.
• Develop tools for market data analysis, post-trade analytics and strategy diagnostics.
• Write scalable code for research, simulation and production-support workflows.
• Optimize systems for large market data and computationally intensive tasks.
• Rapidly prototype new models, signals and trading logic.
• Use LLMs and agentic AI tools to improve research and automation workflows.

Technical Environment :

Python, Pandas, NumPy, SciPy, SQL, Git, API integrations, Matplotlib, Plotly.

Additional tools and libraries:

• Numba / Cython
• Dask / Ray / Polars
• Scikit-learn / XGBoost / LightGBM
• PyTorch / TensorFlow
• TA-Lib / vectorbt / Backtrader / Zipline
• QuantLib
• Shell / Bash scripting
• C++ exposure is a plus

Preferred Skills :

• Experience with algorithmic trading systems or back testing frameworks.
• Experience with market data or tick-level datasets.
• Familiarity with statistical analysis, machine learning and model validation.
• Knowledge of database systems and structured/unstructured data.
• Exposure to cloud platforms or distributed computing.
• Awareness of LLMs, prompt workflows, RAG+ or agentic AI systems.
• Strong problem-solving ability, attention to detail and a fast-learning mindset.

Ideal Background :

• 1–4 years of experience in software development, data engineering, quantitative systems, or AI engineering.
• Strong programming ability with experience handling large datasets and analytical systems.
• Comfortable working in high-ownership environments with rapid iteration.
• Strong foundation in mathematics, statistics, computer science, or a related quantitative field.

Compensation :

Competitive salary with performance-based incentives depending on contribution and impact.