Senior Quantitative Developer

QSentia | AI Investment Intelligence Platform
Equity Based | Pre Seed | Remote | Founding Team

About QSentia

QSentia is building an AI powered investment intelligence platform for family offices, wealth advisors, hedge funds, and institutional investors. Our platform combines reinforcement learning, machine learning, adaptive portfolio risk management, explainable AI, model observability, and institutional investment workflows across equities, futures, digital assets, and other markets.

Our goal is to build the trusted infrastructure through which professional investors can evaluate, deploy, monitor, and govern AI driven investment strategies.

About the Role

We are seeking a Senior Quantitative Developer to join QSentia’s founding team and help turn quantitative research into reliable, production ready investment systems.

You will work across research, software engineering, data infrastructure, portfolio construction, risk management, backtesting, and execution. This role is ideal for someone who can both develop sophisticated quantitative models and build the engineering systems required to operate them in live or paper trading environments.

You will work closely with the Founder, Chief Technology Officer, Chief Data Officer, quantitative researchers, and machine learning engineers.

Key Responsibilities

• Develop and productionize systematic investment strategies across equities, futures, options, digital assets, and multi asset portfolios

• Convert quantitative research and reinforcement learning models into robust trading and portfolio management systems

• Build reliable backtesting, walk forward validation, paper trading, and performance attribution frameworks

• Develop portfolio construction, position sizing, risk budgeting, volatility targeting, and exposure management systems

• Design execution logic, order generation, transaction cost models, slippage assumptions, and broker integrations

• Build data pipelines for market, fundamental, alternative, news, options, and macroeconomic data

• Implement model monitoring, decision telemetry, drift detection, risk alerts, and audit trails

• Improve computational performance for large scale model training, simulation, and portfolio optimization

• Review model assumptions and identify overfitting, leakage, survivorship bias, execution risk, and unrealistic backtest conditions

• Partner with engineering teams to build secure APIs and scalable cloud infrastructure

• Maintain clear documentation, testing standards, version control, and reproducible research workflows

• Contribute to the technical roadmap and help recruit future quantitative engineering talent

Required Qualifications

• Five or more years of experience in quantitative development, systematic trading, financial engineering, or a related technical role

• Advanced Python programming skills and experience writing production quality software

• Strong knowledge of NumPy, pandas, PyTorch, TensorFlow, scikit learn, and quantitative research libraries

• Experience developing backtesting, portfolio construction, risk management, or execution systems

• Strong understanding of financial markets, including equities, futures, options, or digital assets

• Knowledge of statistics, time series analysis, optimization, probability, and machine learning

• Experience working with large financial datasets and market data APIs

• Strong SQL skills and experience with relational and analytical databases

• Experience with Git, automated testing, Docker, cloud computing, and software development practices

• Ability to translate research concepts into dependable production systems

Preferred Qualifications

• Experience at a hedge fund, quantitative asset manager, proprietary trading firm, investment bank, brokerage, or financial technology company

• Experience with reinforcement learning, deep learning, transformers, or sequential decision models

• Experience building systematic long and short portfolios

• Knowledge of market microstructure, execution algorithms, and transaction cost analysis

• Experience with Interactive Brokers, Alpaca, Polygon, Bloomberg, Refinitiv, CME, ICE, or similar platforms

• Familiarity with AWS, SageMaker, EC2, S3, Lambda, ECS, Kubernetes, and CloudWatch

• Experience with C++, Java, Rust, or another high performance language

• Graduate degree in Computer Science, Mathematics, Statistics, Physics, Engineering, Financial Engineering, Economics, or a related field

What Success Looks Like

During the first six months, you will help establish a reliable research to production process, improve the realism and reproducibility of our backtesting environment, and productionize selected QSentia models for institutional pilots.

Over time, you will help build the core quantitative engineering infrastructure supporting model deployment, portfolio management, broker connectivity, monitoring, and institutional scale

What We Offer

• Founding team opportunity with meaningful equity ownership

• Direct influence over the quantitative platform and technical strategy

• Opportunity to work on advanced reinforcement learning and systematic investment models

• Remote first working environment

• High ownership and close collaboration with company leadership

• Opportunity to help build a category defining AI investment technology company

Compensation

This is initially an equity based role while QSentia completes its pre seed financing. Cash compensation will be introduced following funding and will be based on experience, responsibilities, and market benchmarks.