IT Principal Front-Office Engineer

Role: IT Principal Front-Office Engineer

Location: Boston, MA (3X a week onsite)

Duration: 1 Years

Key Responsibilities

• Serve as the technical lead embedded within the Investment Risk team.
• Design, architect, and implement small‑scale applications, prototypes, and production‑grade tools that enhance risk analytics and reporting.
• Develop AI‑enabled workflows using modern agentic programming tools (GitHub Copilot, Claude, etc.).
• Build systems capable of processing large, complex financial datasets.
• Collaborate closely with Risk Directors, risk analysts, and investment teams to deliver high‑value, decision‑ready solutions.
• Rapidly iterate on prototypes, validate concepts, and drive solutions across the finish line.
• Build and maintain robust Python applications, data pipelines, APIs, and visualization tools.
• Develop reporting, dashboards, and data models that support risk management workflows.
• Ensure high-quality code, scalability, maintainability, and adherence to development standards.
• Work onsite in Boston three days per week and participate in 2–3 rounds of onsite interviews.

Qualifications

Required

• 5 years professional experience with Python (must be hands-on and expert level).
• Strong experience with SQL, financial datasets, and data manipulation.
• Experience using Agentic Programming tools (GitHub Copilot, Claude, etc.).
• Experience designing and building application systems in data-rich environments.
• Familiarity with key Python libraries: pandas, NumPy.
• Experience with front‑end development or Pythonic UI/visualization tools (e.g., Plotly, Dash).
• Strong experience with Git and version control.
• Ability to communicate complex technical concepts to both technical and non‑technical stakeholders.
• Ability to work independently with minimal handholding in a fast‑paced environment.
• Strong problem‑solving skills, critical thinking, and attention to detail.
• Understanding of financial markets, multi‑asset class concepts, and investment risk.

Preferred

• Familiarity with:
• Bloomberg, FactSet, Aladdin, eFront, Moody's
• Scikit‑Learn, SciPy, cvxpy (statistical time-series analysis)
• Experience building custom AI tools or AI‑assisted systems.
• Experience in risk analytics, portfolio risk, or investment risk domains.
• Experience developing or maintaining quantitative models, tools, and reports.

Immediate Disqualifiers

• Anyone engaged in personal trading or trading for other firms, hedge funds, or external clients.