Middle Man Jobs (NOW HIRING)

Man Direct Lending is a specialist middle-market direct lender, focused on creating value-added financing solutions to private equity sponsors and investors in private credit since 2014. The firm's approach is highly selective, focusing exclusively on direct lending to the core middle market, structuring loans to non-cyclical businesses in the US operating in recession-resilient sectors, typically with an EBITDA of between US$10 million and US$75 million. As a trusted partner for sponsors, Man Direct Lending has completed financing for over 330 borrowers.

The Man Direct Lending technology team is part of Man's Discretionary Technology department - ~20 engineers across London and New York building the platforms that power Man Group's discretionary investment and client-facing operations. The team works very closely with the front-office investment professionals in New York, as well as the broader Discretionary tech department in the UK.

The team is focused on integration and automation of deal pipelines, data flows and report generation, leveraging the best tools available from Man's technology platform. The technology stack in Man Direct Lending is actively being built out, this is a rare opportunity with a high degree of greenfield work, low levels of legacy maintenance, and plenty of opportunity to actively shape the platform yourself.

Generative AI and LLM-powered tooling form a growing and strategically important part of our work. We are one of the most active AI-adopting engineering teams in Man Group, and the Man Direct Lending team is at the forefront of applying these capabilities to private credit workflows.

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.

• A proponent of strong collaborative software engineering techniques and methods: agile development, continuous integration, code review, unit testing, refactoring and related approaches
• 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

• 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
• 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

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.

• We open-source some of our technology. See https://github.com/man-group
• We regularly talk at leading industry conferences

We offer competitive compensation, a generous holiday allowance, various health and other flexible benefits. We are also committed to continuous learning and development via coaching, mentoring, regular conference attendance and sponsoring academic and professional qualifications.

We are currently refitting our offices in New York, and can expect to move in to a brand new open-plan space in mid-September, prior to which you could expect to be working remotely. In general, Technology roles are expected to be in the office for 3 days a week. However, the specifics can vary based on the role, team, and individual circumstances, and are ultimately subject to the manager's discretion.