The company is building an AI-native platform for finance, a multi-agent system designed to revolutionize how investment teams make decisions. The goal is to empower these teams to operate faster, think deeper, and work smarter by transforming fragmented financial data into actionable insights using autonomous agents.
Requirements
- Have built and scaled production-grade backend systems for data-intensive or real-time applications.
- 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.
- Experience with AI frameworks, LLMs, or multi-agent orchestration platforms (e.g., LangGraph, CrewAI, AutoGen, Haystack, etc.).
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.
Other
- This remote position requires monthly travel to the Bay area or Seattle for in person team meetings.
- Have 3–7 years of backend engineering experience
- Are excited about building intelligent systems with autonomous behavior, not just CRUD apps.
- Enjoy working on complex logic and domain modeling in high-stakes environments like fintech, trading, or enterprise SaaS.
- Exposure to financial data modeling, investment workflows, or alternative data pipelines.
