• Architect distributed systems that power AI agent orchestration, handling complex multi-step workflows with reliability and observability • Design and implement core backend services in Golang for high-performance, concurrent operations and Python for AI/ML integrations and data pipelines • Build robust APIs and service interfaces that abstract AI capabilities for consumption by multiple clients and internal systems • Own the technical roadmap for backend infrastructure supporting LLM integrations, vector search, and real-time data processing • Establish architectural patterns and standards for service design, data modeling, and inter-service communication • Drive system scalability and reliability, implementing caching strategies, database optimization, and async processing patterns • Build data pipelines that process equity data, embeddings, and user interactions to continuously improve AI model performance • Collaborate cross-functionally to translate business requirements into technical architecture and make pragmatic build vs. buy decisions • Mentor engineers on backend best practices, system design, and technical decision-making