Note: The job is a remote job and is open to candidates in USA. Genios AI is on a mission to build an AI-native platform for finance, transforming how investment teams operate. The Backend Engineer will architect and develop scalable backend systems, build APIs, and collaborate with cross-functional teams to integrate financial logic and user workflows. Responsibilities Architect and develop scalable backend systems using Python and modern cloud-native tools Build APIs, orchestration layers, and data pipelines that support autonomous agents and real-time financial analytics Translate complex financial logic into clear, maintainable, and performant code Collaborate with cross-functional teams—including ML, data, and product—to integrate LLMs, financial logic, and user workflows Own the performance, reliability, and maintainability of mission-critical systems Drive best practices in architectural decisions, testing, devops practices, IaC and system observability Skills Have 3–7 years of backend engineering experience Have built and scaled production-grade backend systems for data-intensive or real-time applications Are excited about building intelligent systems with autonomous behavior, not just CRUD apps Have strong proficiency in Python and experience building distributed backend systems Think in abstractions and API contracts before diving into implementation, and have experience designing and consuming clean, well-structured interfaces (REST, GraphQL, or RPC) Have experience with containerization (Docker), orchestration (Kubernetes), and event-driven systems (e.g., Kafka) Have deep understanding of relational databases (e.g., PostgreSQL) and caching systems (e.g., Redis) Have a strong grasp of performance tuning, code quality, automated testing, CI/CD practices, and building systems that are secure, observable, and production-ready Enjoy working on complex logic and domain modeling in high-stakes environments like fintech, trading, or enterprise SaaS Experience with AI frameworks, LLMs, or multi-agent orchestration platforms (e.g., LangGraph, CrewAI, AutoGen, Haystack, etc.) Exposure to financial data modeling, investment workflows, or alternative data pipelines Company Overview Financial Superintelligence to automate your most complex finance workflows. It was founded in undefined, and is headquartered in Santa Clara, CA, US, with a workforce of 11-50 employees. Its website is https://geniosai.co. Apply To This Job