Job Description:

Quant Developer – AI / KDB / Python

The Team

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.

The Role

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.

• 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

The Expertise You Have:

• 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
  • Real‑time and historical analytics
• Strong Python skills for:
  • Quantitative analysis
  • AI / ML model development
  • 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

 

The Skills You Bring:

• 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.

Fidelity’s Onsite Working Model
Fidelity is transitioning to a full-time onsite working model through a phased rollout across regions and roles. Currently, some roles and locations require 100% onsite presence, while others require less. Onsite expectations are likely to evolve as the rollout continues. This transition does not apply to fully remote roles.

The base salary range for this position is $107,000-216,000 USD per year.  

Placement in the range will vary based on job responsibilities and scope, geographic location, candidate’s relevant experience, and other factors.

Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.   

We offer a wide range of benefits to meet your evolving needs and help you live your best life at work and at home.  These benefits include comprehensive health care coverage and emotional well-being support, market-leading retirement, generous paid time off and parental leave, charitable giving employee match program, and educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career.  Note, the application window closes when the position is filled or unposted.

Certifications:

Category:Information Technology