Backend Engineer

Genios AI

137d • Remote

About The Position

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. Note: This remote position requires monthly travel to the Bay area or Seattle for in person team meetings.

Requirements

• 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.

Nice To Haves

• 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.

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed