Principal Front-Office Engineer - Investments Technology (Private Markets)
Liberty Mutual · Boston, MA, US
About this role
## Principal Front-Office Engineer — Investments Technology (Private Markets) ### Overview Liberty Mutual is seeking a **Principal Front-Office Engineer** to join the **Private Markets Technology** team, working closely with the **Portfolio Strategy & Management (PSM)** team. You’ll design and build small-scale applications and **POCs** that evolve into production-ready tools to improve **private markets portfolio analysis**, **AI-enabled workflows**, and **reporting systems/processes** across **private equity, private credit, real estate, and infrastructure**. This is a highly iterative role under LMI’s **Embedded Tactical Development (ETD)** framework—working directly with the business, choosing the right tools/stack, and shipping in short cycles (no sprint planning or scrum ceremonies). > **Location:** Boston (hybrid — **3 days/week in office**) ### Responsibilities - Embed with the PSM team to understand **portfolio strategy, pacing, liquidity, and performance workflows**, then translate them into well-scoped tools delivered iteratively. - Design and build **full-stack Python applications**, **data pipelines**, and **decision-ready reports** on enterprise platforms (e.g., **GitHub**, **GitHub Actions CI/CD**, **Snowflake**, **Azure AD-secured web apps**). - Help analysts harden **AI-generated prototypes/POCs** into **reliable, maintainable, institutional-grade** applications. - Implement **output validation**, document **assumptions/limitations**, and add basic **runtime logging** for decision-support tools. - Provide best-effort operational support and remediate vulnerabilities within enterprise **SLAs**. - Maintain clean, well-organized repositories (consistent structure, automated linting/formatting, semantic versioning, tagged releases, and up-to-date documentation). - Contribute to and reuse shared utilities (e.g., connectors, authentication helpers, report distribution) with other embedded engineers. ### Qualifications - **5+ years** professional experience programming in **Python** (robust, efficient code for large financial datasets). - Strong problem-solving and the ability to work independently with minimal handholding. - Effective communication with technical and non-technical stakeholders. - Strong attention to detail and ability to manage multiple priorities in a fast-paced environment. - **Python libraries:** **pandas**, **NumPy** (required). - **Front-end/UX:** required; experience with **Plotly** and/or **Dash** preferred. - **Version control:** **Git** (required). - **CI/CD & cloud:** **GitHub Actions** preferred; cloud deployment preferred. - **Agentic programming tools:** **GitHub Copilot** and/or **Claude** (required). - Demonstrated ability to partner with business teams to convert AI artifacts (prototypes/POCs) into production-ready applications. - Experience designing/building/scaling systems in data-rich environments, including custom AI tools. - **SQL:** required. - **Snowflake:** plus. - Familiarity with private markets data platforms (e.g., **eFront, PitchBook, DealCloud**) strongly preferred. - Statistical/time-series analysis with Python libraries (e.g., **scikit-learn, SciPy, cvxpy**) preferred; **Monte Carlo/scenario cash-flow modeling** is a plus. - Solid understanding of private markets concepts (fund structures, capital calls/distributions, J-curve, commitment pacing, performance metrics like **IRR, MOIC/TVPI, DPI, PME**). - Practical experience building models/tools/reports using quantitative/
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