Principal Front Office Engineer - Investment Innovation, Integration & Trading

Liberty Mutual Insurance•Boston, MA

9d•$175,000 - $225,000•Hybrid

About The Position

Liberty Mutual Investments Technology is seeking a Principal Front-Office Engineer to serve as the technical lead embedded within the Investment Innovation, Integration & Trading (I3T) team. The role drives the design and implementation of small-scale proofs of concept and prototypes supporting the fixed income portfolio, investment analysis, AI-enabled workflows, and reporting systems and processes. The engineer will partner with analysts and investment teams to improve their use of AI, help make artifacts more technically sound, and develop robust systems and tools that scale prototypes into production-ready applications. This is a hands-on software architect and builder role focused on designing systems, iterating rapidly, and delivering solutions for analytics, reporting, and investment decision-making. It is suited to a Lead or Senior Engineer who wants to drive technical direction as an individual contributor rather than move into management. The position is based in Boston and has a hybrid arrangement requiring three days per week in the office.

Requirements

At least 8 years of professional programming experience in Python, with the ability to write efficient, robust code for processing and analyzing large financial datasets.
Experience with Python libraries including pandas and NumPy.
Experience with front-end development and user experience (UX) design.
Experience using version control with Git.
Experience using agentic programming tools such as GitHub Copilot or Claude.
Strong SQL skills.
Ability to partner with business teams to convert AI-generated artifacts, such as prototypes and proofs of concept, into production-ready applications.
Ability to design, build, and scale application systems in data-rich environments, including custom AI tools.
Solid understanding of financial markets and foundational knowledge across fixed income, private equity, and private credit investment domains.
Practical experience developing and maintaining models, tools, and reports that demonstrate understanding of quantitative techniques, methods, statistics, and econometrics.
Excellent problem-solving skills; ability to think critically and independently and act with minimal handholding.
Effective communication skills, including the ability to explain complex ideas and analysis to technical and non-technical stakeholders.
Strong attention to detail and organization, and ability to manage multiple tasks and priorities in a fast-paced environment.
Bachelor’s or Master’s degree in a technical or business discipline, or equivalent experience.

Nice To Haves

Hands-on experience developing within Bloomberg’s BQuant environment.
Experience writing and maintaining BQL queries, leveraging PyBQL, and working with the Bloomberg data ecosystem.
Experience with Pythonic front-end and data visualization libraries such as Plotly and Dash.
Experience developing applications for investment management firms or the financial services industry more broadly.
Familiarity with financial data platforms such as Bloomberg, FactSet, Aladdin, eFront, or Moody’s, financial databases, and data manipulation techniques.
Experience with statistical and time-series data analysis using Python libraries such as Scikit-Learn, SciPy, or cvxpy.
Experience bridging rapid AI-developed prototypes into quality full-stack applications.

Responsibilities

Lead technical design and implementation of proofs of concept and prototypes for the I3T team.
Support the fixed income portfolio, investment analysis, AI-enabled workflows, and reporting systems and processes.
Partner with analysts and investment teams to improve their day-to-day use of AI and help them build technically sound artifacts.
Build robust systems and tools that scale prototypes into production-ready applications.
Design, rapidly iterate on, and deliver quality solutions for analytics, reporting, and investment decision-making.
Design, build, and scale application systems in data-rich environments, including custom AI tools.
Develop and maintain models, tools, and reports using quantitative techniques, methods, statistics, and econometrics.