My Client in the US Connecticut is looking for:

Software Engineer

**Full-time On-site***

Stamford, Connecticut

$160K - $230K (OTE: $180K - $250K)

**** No working visa sponsorship available, 5 day a weel onsite Connecticut*****

Role Requirements

• Looking for a full-stack generalist with experience in the T3 stack (TypeScript, Python, AWS).
• Proficiency in Python is necessary; familiarity with AI engineering, automation, and finance is a plus.

Required:

2 - 7 years of experience in full- stack software development experience, with proficiency in the T3 stack and python

Must have: Ability to read and write Python for scripting and automation

Experience with relational databases and writing production- quality SQL

Nice to have

• Experience with AI/LLM APIs to build automations or agentic workflows
• Finance, fintech, or quant- adjacent company background (including additional major/minor in undergrad)

Question:

• What's something cool you've built outside of a professional context — whether it's a personal tool, a side project, a sports betting model, or anything else you made just because you were curious?
• What's your familiarity or interest in financial markets, investing, or other data-driven/quantitative domains like sports analytics?

My client is an investment firm founded 8.5 years ago that manages approximately $700 million in assets. The firm operates as a combination of hedge fund and private equity, with a flexible mandate spanning fundamental equities, credit investing, and private equity investing.

They have delivered top 1 percentile net returns since inception, with high-20s net annualized performance. The firm has grown from $5 million on day one to ~$700 million under management, and counts some of the top universities in the world among its investors.

There is the quantitative research and technology arm supporting the Opportunities Fund. Their work spans three core areas:

• Portfolio Support & Analytics: Serving as a research partner to the portfolio manager and fundamental analyst team, identifying areas of strength and weakness through rigorous quantitative analysis and building tools to improve core fund performance.
• Risk Management: Designing and deploying custom factor hedges, constructing bespoke hedge baskets tailored to the fund's specific risk profile.
• Alpha Factor Research: Developing proprietary alpha factors using fundamental and alternative data sources to identify high- and low-quality businesses, with potential to operate as standalone systematic investment strategies.

The firm is investing heavily in building proprietary software tools and AI integrations across every aspect of the research process — from idea generation to position sizing to LLM integrations — creating real technological edge in investment research.

Current team size 10

Founded 2017