Principal Software Engineer
Fidelity Investments is a privately held, Boston-headquartered financial services company providing investing, trading, retirement, wealth management, brokerage, workplace benefits, custody and clearing, and digital-asset services.
Maintainer signals as of 9/25/2026
About Fidelity Investments
Fidelity serves individual investors, employers, wealth-management firms, institutions, innovators, and charitable donors through diversified financial-services businesses. Current offerings include brokerage and trading, mutual funds and exchange-traded products, retirement and workplace savings, financial planning and advice, wealth management, institutional custody and clearing, and crypto/digital-asset products.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead the hands-on design and development of resilient trading infrastructure. You will optimize KDB databases and q analytics, develop Python AI and quantitative models, build backtesting frameworks, integrate models into production pipelines, and mentor engineers while supporting production systems.
Requirements
- Bachelor's degree in Mathematics, Computer Science, Engineering, Information Technology, or equivalent.
- 10 years of professional experience in quantitative finance or trading systems.
- Advanced KDB/q proficiency, including time-series modeling, high-performance querying, joins, and analytics.
- Python skills for quantitative analysis, AI and machine-learning model development, and KDB integration.
- Experience with large-scale, high-frequency, or noisy datasets.
- Git, testing, and modular software design experience.
- Experience with AI developer-assist tools such as GitHub Copilot.
- Experience with GitHub, Maven, Jenkins, Artifactory, uDeploy, and CI/CD tools.
- AWS or other cloud platform experience.
- Familiarity with Java, Linux, shell scripting, and production support.
Responsibilities
- Design, develop, and optimize KDB databases and q analytics for trading and market data.
- Develop Python-based AI and quantitative models for research, prediction, classification, and signal generation.
- Apply machine learning to time-series data.
- Build research and backtesting frameworks using historical data.
- Translate quantitative and machine-learning research into production systems.
- Integrate AI models into real-time and batch pipelines.
- Optimize analytics and model evaluation for performance, stability, and scalability.
- Collaborate with quantitative, product, and engineering partners on model deployment and monitoring.
- Lead technical design, mentor engineers, and support production systems and on-call rotations.
Benefits
- Comprehensive health care coverage.
- Emotional well-being support.
- Retirement benefits.
- Paid time off.
- Parental leave.
- Charitable giving employee match program.
- Student loan repayment.
- Tuition reimbursement.