3 дня назад
Software Engineer (AI/Fintech)
160 000 - 230 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Software Engineer (AI/Fintech): Building internal full-stack tools for investment research and risk management with an accent on TypeScript, React, Next.js, Python, SQL, and modern LLM APIs. Focus on developing new workflows, designing relational databases, building AI-enabled automations, and owning production software across frontend, backend, deployment, and support.
Location: Onsite in Stamford, Connecticut, five days per week
Salary: $160,000–$230,000 annual base salary plus discretionary bonus
Company
builds software supporting investment research and risk management workflows.
What you will do
- Maintain and improve full-stack applications for investment research and risk management.
- Build new internal tools, products, and workflows from scratch.
- Develop modern web applications with TypeScript, React, and Next.js.
- Use Python for scripting, automation, and data-related workflows.
- Design and query relational databases with production-quality SQL.
- Build AI-enabled automations using OpenAI, Anthropic, and other LLM APIs while supporting production systems.
Requirements
- 2–7 years of professional full-stack software development experience.
- Strong TypeScript and React experience, ideally including Next.js.
- Practical Python experience for scripting or automation.
- Strong relational database and SQL skills.
- Experience owning production software across frontend and backend development.
- An undergraduate degree in Computer Science with a GPA above 3.0.
Nice to have
- Experience with tRPC, Prisma, or a comparable modern TypeScript stack.
- Exposure to OpenAI, Anthropic, other LLM APIs, agentic workflows, or AI-enabled automation.
- AWS, Bash, CI/CD, or Airflow experience.
- Background or demonstrated interest in finance, fintech, investment research, or quantitative systems.
Culture & Benefits
- Significant ownership from day one.
- Direct access to decision-makers in a small engineering environment.
- Opportunity to build new products rather than only maintain existing systems.
- Hands-on exposure to investment research and quantitative workflows.
- Minimal bureaucracy and practical experience with modern AI engineering.
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