AI Full Stack Software Engineer

Software Engineer, Investment TechnologyThe OpportunityA Stamford-based investment firm managing approximately $3 billion in assets is expanding its engineering capabilities. The organization has more than 50 employees, with technology working closely alongside the investment side of the business.This position is built for a software engineer who enjoys taking a problem from an initial conversation through a finished product. Rather than working on a narrow component of a larger system, you'll develop software used directly by portfolio managers, researchers, and other investment professionals.Projects sit at the intersection of software engineering, quantitative investing, data, and applied AI.What You'll BuildYou'll develop internal software that helps investment teams research ideas, understand portfolios, evaluate risk, and make better use of financial data.Your work may include:Creating web applications for portfolio analysis and investment researchDeveloping tools for monitoring risk, exposures, and portfolio characteristicsBuilding software that supports quantitative analysis and portfolio constructionTurning investment and research requirements into usable internal productsDeveloping interfaces that make complex datasets easier to explore and interpretBuilding APIs, backend services, database functionality, and data pipelinesIncorporating large language models into internal applications and automated workflowsTaking features through architecture, development, testing, release, and iterationContributing to technical architecture and engineering practices as the platform developsYou'll work directly with the professionals using what you build. That means understanding the underlying business problem is just as important as writing the code.What We're Looking ForWe're targeting engineers with roughly 2 to 4 years of professional software development experience and genuine full-stack experience.You should have:Production experience with TypeScript and ReactExperience working across both user-facing applications and backend systemsThe ability to translate complex requirements into clean, practical softwareExperience with Python, SQL, or comparable backend and data technologiesA solid foundation in application design, testing, debugging, and maintainable codeComfort taking meaningful ownership without a large engineering organization around youAn interest in markets, investing, quantitative problems, trading, or other data-heavy fieldsA degree in computer science, mathematics, engineering, or another technical discipline can be helpful, but it isn't required.We also value engineers who build things because they're curious. Personal applications, open-source contributions, technical experiments, and independent projects can all demonstrate that.Technical EnvironmentThe platform uses a modern web stack with TypeScript and Python as core languages. Technologies relevant to the environment include React, Next.js, tRPC, Prisma, Tailwind CSS, SQL, and AWS.You aren't expected to arrive with experience in every part of the stack. Strong TypeScript and React experience matters most. Familiarity with Next.js, tRPC, Prisma, or comparable full-stack technologies would be useful.Applied AIGenerative AI is being incorporated directly into the firm's internal software rather than treated as a standalone research initiative.Engineers may build applications that use large language models to automate workflows, assist with analysis, retrieve information, and support investment-related processes. Relevant experience could include production LLM integrations, model APIs, retrieval-based applications, agent workflows, LangChain, or similar technologies.Hands-on experimentation counts here too. Candidates who have built their own AI applications or incorporated these technologies into independent projects are encouraged to discuss that work.How the Team WorksThis is a hands-on engineering environment with close access to the investment professionals who use the technology. Engineers are expected to understand the problem, propose an approach, build the solution, and continue improving it based on real-world use.The position is full-time and onsite in Stamford, Connecticut, five days per week. The firm has more than 50 employees and approximately $3 billion in assets under management.