Front Office Engineer (Boston)
Seaglass Technology Partners, LLC, Boston, MA, United States
W2 candidates only. Must be authorized to work in the U.S without employer sponsorship now or in the future. This Boston-based role has a hybrid work arrangement (3 days per week in office). Onsite interviews required.
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
Effective communication skills, with the ability to clearly articulate complex ideas and analysis to both technical and non-technical stakeholders.
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 Agentic Programming tools (Github Copilot, Claude) required.
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.
Experience working on an investment team or company.
Practical experience in developing and maintaining models, tools, and reports that showcase a deep understanding of quantitative techniques, methods, statistics and econometrics.
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
Effective communication skills, with the ability to clearly articulate complex ideas and analysis to both technical and non-technical stakeholders.
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 Agentic Programming tools (Github Copilot, Claude) required.
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.
Experience working on an investment team or company.
Practical experience in developing and maintaining models, tools, and reports that showcase a deep understanding of quantitative techniques, methods, statistics and econometrics.