Software Engineer

Man Group•New York, NY

1d•$130,000 - $150,000•Hybrid

About The Position

This is an engineer role within the Man Direct Lending technology team in New York, working side-by-side with investment professionals and in collaboration with the wider Discretionary tech department in the UK. You will contribute to building and maintaining production systems across the full stack — data pipelines, analytics platforms, web tools, and AI-powered automation — while developing a close understanding of the investment team’s workflows and helping them embrace new technology. The target technology stack is on Linux with the majority of code written in Python, using the full scientific stack like Pandas and scikit-learn. We also have C# integrations with Excel, and several web-based tools using a variety of languages and frameworks like React, Streamlit, FastAPI and Django. We are heavy users of Man’s own high performance proprietary database ArcticDB, alongside traditional RDBMS’. Generative AI forms a core and expanding part of our estate — we actively build and ship LLM-powered agents, document intelligence tools, and vector search applications for our investment teams. All our code is deployed using Kubernetes and modern cluster computing frameworks. Man Technology has a small company, no-attitude feel. It is flat structured, open, transparent and collaborative, and you will have plenty of opportunity to grow and have enormous impact on what we do. We are actively engaged with the broader technology community.

Requirements

A proponent of strong collaborative software engineering techniques and methods: agile development, continuous integration, code review, unit testing.
Strong knowledge of Python.
Proficient on Linux platforms with knowledge of various scripting languages.
Experience of data analysis techniques along with relevant libraries e.g. NumPy/SciPy/Pandas.
Experience of web-based development and visualisation technology for portraying large and complex data sets and relationships.
Experience building with or integrating AI/LLM-based tools — we are active early adopters of AI-assisted development and expect engineers at all levels to engage with these tools.
Intellectually robust with a keenly analytic approach to problem solving.
Self-organised with the ability to effectively manage time across multiple projects and with competing business demands and priorities.
Strong interpersonal skills; able to establish and maintain a close working relationship with investment professionals and senior business stakeholders.
Confident communicator; able to argue a point concisely and deal positively with conflicting views.

Nice To Haves

Experience in private credit or direct lending investment.
A keen interest and understanding of financial markets and instruments.
Relevant mathematical knowledge e.g. statistics, optimisation algorithms.
Familiarity with LLM agent frameworks, vector search, or RAG pipelines.
Experience with Kubernetes and containerisation.
Experience with Airflow for scheduled data pipelines.
C#/.NET familiarity — some systems across the wider team are built in .NET.
Strong academic record and a degree with high mathematical and computing content e.g. Computer Science, Mathematics, Engineering or Physics, or equivalent worked experience.
Craftsman-like approach to building software; takes pride in engineering excellence and instils these values in others.
Demonstrable passion for technology e.g. personal projects, open-source involvement, or active engagement with the AI tooling space.

Responsibilities

Contribute to building and maintaining production systems across the full stack — data pipelines, analytics platforms, web tools, and AI-powered automation.
Develop a close understanding of the investment team’s workflows and help them embrace new technology.
Build and ship LLM-powered agents, document intelligence tools, and vector search applications for investment teams.
Deploy code using Kubernetes and modern cluster computing frameworks.

Benefits

Competitive compensation
Generous holiday allowance
Various health and other flexible benefits
Continuous learning and development via coaching, mentoring, regular conference attendance and sponsoring academic and professional qualifications.
Competitive holiday entitlements
Pension/401k
Life and long-term disability coverage
Group sick pay
Enhanced parental leave
Long-service leave
Private medical coverage (depending on location)
Discounted gym membership options (depending on location)
Pet insurance (depending on location)