Principal Quant Developer

Fidelity • Boston, MA

3d • Onsite

About The Position

The Quantitative Research & Investing Technology (QRIT) team within Fidelity's Asset Management Technology group is seeking a highly motivated and curious Principal Quantitative Developer. In this role you will contribute to a dynamic and fast-paced development team supporting researchers in prototyping and delivering new systematic investment strategies. You will provide high impact solutions on various projects including alpha research, portfolio construction, and risk management. Your technology knowledge covers a broad spectrum of technologies, including Python and PL/SQL databases, positioning you as a full-stack software engineer who capitalizes on enterprise technology. You are committed to constructing high-quality, scalable, robust, resilient and efficient analytical and software solutions that propel investment processes forward.

Requirements

• A Bachelor's degree in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, Statistics, Engineering, or a closely related field and six (6) years of experience as a Senior Quant Developer or similar role.
• Alternatively, a Master's degree (or equivalent foreign education) in the same fields, accompanied by four (4) years of experience as a Lead Quantitative Development or similar role.
• Building high-quality, robust, and efficient systems and solutions for financial investment decisions, utilizing Python, PL/SQL databases, and quantitative techniques.
• Expert in Python with experience across the development stack (full stack).
• Exposure to object-oriented programming (OOP) and design patterns.
• Experience in at least one unit testing framework and understanding of test-driven development (TDD) concepts and methodologies.
• Strong, demonstrable knowledge of mathematics, statistics, and quantitative finance (core to this role).
• Deep understanding of quantitative techniques and methods, statistics and econometrics including probability, linear regression and time series data analysis.
• Skilled in SQL databases (Oracle).
• Skilled in batch and API technologies: such as batch scheduling (using Autosys and Airflow) and creating REST APIs (using FAST API and Flask).
• Proven ability to construct and manage robust data pipelines and event-driven workflows.
• Proven expertise in system design and cloud architecture on AWS, leveraging resources including Lambda, S3, EKS, and EC2.
• Experience in containerization with Docker.
• Experience in CI/CD pipelines (using Linux and Jenkins), code versioning using GitHub.
• Familiarity with observability and production support (logging, tracing, monitoring, alerting).
• Strong communication and problem-solving skills.

Nice To Haves

• Working knowledge of R is a plus.
• Experience with industry-scale optimization libraries (e.g., Gurobi, CPLEX, Axioma, SciPy) and portfolio construction / optimization is a strong plus.
• Progress towards CFA (or equivalent) a plus.
• Snowflake, NoSQL, or Graph databases a plus.
• Orchestration with Kubernetes a plus.
• Experience in Infrastructure as Code methodologies for consistent and scalable infrastructure management.
• MLOps & AI (Preferred)
• Operationalizing ML models and pipelines on AWS using modern MLOps principles, including SageMaker (training, deployment, model registry, monitoring) and Bedrock (foundation model access, fine-tuning) and production lifecycle management.
• Familiarity with experiment tracking and model versioning tools (e.g., MLflow).
• Deploying and operationalizing LLM-based / agentic workflows in production (e.g., LangGraph, LangChain), including orchestration, tool use, monitoring, and evaluation.
• Awareness of responsible AI governance practices.

Responsibilities

• Contribute to a dynamic and fast-paced development team supporting researchers in prototyping and delivering new systematic investment strategies.
• Provide high impact solutions on various projects including alpha research, portfolio construction, and risk management.
• Construct high-quality, scalable, robust, resilient and efficient analytical and software solutions that propel investment processes forward.
• Analyze and design systems to implement quantitative models for systematic financial investments using Python, including time series forecasting models, multi-asset class portfolio construction strategies, risk management tools, alpha research, and simulation-based algorithms.
• Deliver production quant solutions in a systematic investing or trading environment.
• Construct and manage robust data pipelines and event-driven workflows.
• Implement CI/CD pipelines (using Linux and Jenkins), code versioning using GitHub.
• Manage infrastructure using Infrastructure as Code methodologies for consistent and scalable infrastructure management.
• Operationalize ML models and pipelines on AWS using modern MLOps principles, including SageMaker (training, deployment, model registry, monitoring) and Bedrock (foundation model access, fine-tuning) and production lifecycle management.
• Apply ML to quantitative investing: time series forecasting, anomaly detection, and predictive analytics.
• Deploy and operationalize LLM-based / agentic workflows in production (e.g., LangGraph, LangChain), including orchestration, tool use, monitoring, and evaluation.
• Partner effectively with quant researchers and investment teams to deliver solutions through the full development lifecycle.

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior