Principal Software Engineer

Fidelity Wealth’s Trade Management Engineering group is responsible for building world-class electronic trading solutions for Fidelity’s Capital Markets division. We are a high-performing, fast-paced technology team working with cutting-edge tools to deliver low-latency, high-throughput trading platforms. Our work spans across internal and external teams to build seamless, end-to-end electronic trading workflows. We are seeking a highly experienced software engineer to lead the design and development of next-generation trading systems. This is a hands-on technical leadership role focused on building scalable, resilient, and high-performance trading infrastructure. You’ll collaborate across teams, mentor engineers, and drive innovation in a mission-critical environment.

Responsibilities

Collaborate across teams, mentor engineers, and drive innovation in a mission-critical environment; Design, develop, and optimize KDB databases and q analytics for high-volume trading and market data; Develop Python-based AI and quantitative models for research, prediction, classification, and signal generation; Apply machine learning techniques to time-series data (feature engineering, model training, evaluation); Build research and backtesting frameworks integrating AI models with historical data; Translate quantitative and ML research into robust, production-ready systems; Integrate AI models into real-time and batch pipelines; Optimize analytics and model evaluation for performance, stability, and scalability; Collaborate with quants, product owners, and engineering teams on model deployment and monitoring

Requirements

Bachelor’s degree in Mathematics, Computer Science, Engineering, Information Technology, or equivalent; 10 years professional experience in quantitative finance or trading systems; Advanced proficiency in KDB/q including time-series data modeling, high-performance querying and joins, and real-time and historical analytics; Strong Python skills for quantitative analysis, AI/ML model development, and integration with KDB and downstream systems; Experience working with large-scale, high-frequency, or noisy datasets; Solid software engineering practices (Git, testing, modular design); Worked with AI developer assist tools (e.g. GitHub Copilot); Experience with CI/CD tools such as GitHub, Maven, Jenkins, Artifactory, and uDeploy; Hands-on experience in AWS or other cloud platforms; Familiarity with object-oriented programming languages such as Java; Experience in Linux, shell scripting, and production support experience; A strong quantitative mindset with practical AI application skills; Ability to bridge research, machine learning, and production systems; Comfort working on front-office or research-critical infrastructure; Clear communicator with quants, traders, and engineers; Willingness to support production systems and participate in on-call rotations, including occasional weekend support

Benefits

Comprehensive health care coverage and emotional well-being support; market-leading retirement; generous paid time off and parental leave; charitable giving employee match program; educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career; bonus or other variable compensation