About the role

Role overview

Finstock is hiring a Software Engineer to build, maintain, and scale its AI-powered financial research and market intelligence platform. You’ll work across backend services, APIs, product features, data integrations, internal tools, and user-facing workflows, collaborating with engineering, product, data, AI, and analyst teams.

Key responsibilities

Design, build, test, and maintain platform features for financial research and market intelligence
Develop secure, reliable, and scalable backend services and APIs
Build and improve user-facing workflows, dashboards, research tools, and analytics
Integrate market data, company data, research metadata, analytics outputs, and approved third-party APIs
Translate product and research requirements into production-ready software with cross-functional teams
Write clean, maintainable, tested, and well-documented code
Participate in code reviews, architecture discussions, and technical planning/design
Improve performance, reliability, observability, error handling, and security
Support analyst workflow tooling, research automation, charting, data review, and intelligence features
Troubleshoot production issues and assist with incident resolution
Contribute to CI/CD, testing standards, documentation, and engineering best practices
Follow internal security, privacy, confidentiality, and data-handling requirements

Required qualifications

3+ years of professional software engineering experience (backend/full-stack or related)
Strong proficiency in at least one modern language: Python, TypeScript, JavaScript, Java, Go, or C#
Experience building production-grade APIs, backend services, web apps, or internal engineering tools
Experience with relational databases such as PostgreSQL, MySQL, or similar
Familiarity with frontend or full-stack development

Nice-to-haves

Not explicitly stated in the provided text.

About Finstock, Inc.

Finstock, Inc. builds AI-powered financial research, trading analytics, quantitative research, and market intelligence tools for analysts and institutions. Its platform depends on secure, scalable software systems, reliable APIs, secure data workflows, and high-quality engineering across analytics and research use cases.