Title: Full Stack Engineer
Location: Boston, MA 02116 (Hybrid-3 days onsite)
Duration: 12 Months
Payrate: $82.14/hr
Job Description:
We are seeking a highly skilled and motivated Principal Front-Office Engineer to join our prestigious investment firm. As a Principal Front-Office Engineer, you will serve as the technical lead embedded within the Risk team, driving design and implementation of small-scale applications and proof of concepts that will improve risk analysis, develop AI-enabled workflows, and enhance reporting systems & processes.
You will work closely with risk analysts and investment teams, but your primary focus will be building robust systems and tools that power risk infrastructure, analytics, and decision-ready reporting. We’re looking for a hands-on software architect and builder who has experience designing systems, rapidly iterating over them and delivering them across the finish line. This role is ideal for a Lead or Senior Engineer who thrives as an individual contributor and wants to drive technical direction without moving into management.
Qualifications
• Excellent problem-solving skills, with the ability to think critically, independently, and act with minimal handholding.
• Effective communication skills, with the ability to clearly articulate complex ideas and analysis to both technical and non-technical stakeholders.
• Strong attention to detail, organization, and the ability to manage multiple tasks and priorities in a fast-paced environment.
• Full-stack development knowledge with a minimum of 5+ years professional experience programming in Python demonstrating the ability to write efficient and robust code able to process and analyze large financial datasets.
• Experience with key Python Libraries (pandas, NumPy) required
• Experience in front-end development and user experience (UX) design required; experience with Pythonic front-end and data visualization libraries (e.g., Plotly, Dash) preferred.
• Experience using Version Control (Git) required.
• Experience using Agentic Programming tools (Github Copilot, Claude) required.
• Proven ability to design, build, and scale application systems in data-rich environments including custom AI tools.
• Strong SQL skills required with a familiarity of financial data platforms (such as Bloomberg, FactSet, Aladdin, eFront, Moodys), financial databases, and data manipulation techniques preferred. Experience with statistical and time-series data analysis using pythonic libraries (such as Scikit-Learn, SciPy, cvxpy) is preferred.
• Solid understanding of financial markets and multi-asset investment risk domain.
• Practical experience in developing and maintaining models, tools, and reports that showcase a deep understanding of quantitative techniques, methods, statistics and econometrics