Staff Backend Engineer, Pulley

• 7+ years of backend engineering experience building production systems at scale
• Expert-level proficiency in Pythonfor AI/ML integrations, data processing, and scripting
• Strong Python skills with deep understanding of concurrency patterns, performance optimization, and production Go services
• Proven experience designing and building distributed systems, including microservices architecture, event-driven systems, and async workflows
• Deep knowledge of API design (REST) and service-to-service communication patterns
• Demonstrated experience building backend systems that integrate LLMs and AI capabilities into production applications
• Hands-on work with agent frameworks, LLM orchestration, and AI service reliability
• Familiarity with RAG architectures, vector databases (Pinecone, Weaviate, Qdrant), and embeddings pipelines
• Experience building evaluation frameworks and observability for AI systems
• Understanding of prompt engineering and LLM API optimization (latency, costs, rate limits)
• Track record of architecting greenfield services from concept to production with scalability and maintainability in mind
• Experience with database design and optimization (PostgreSQL, Redis, time-series databases)
• Strong foundation in system observability, monitoring, and debugging distributed systems in production
• Proven ability to lead technical initiatives and establish engineering best practices
• Experience mentoring engineers and elevating team technical capabilities

Desirable

• We're looking for a Staff Backend Engineer who will architect and build the foundational systems powering our AI-native product
• You'll own the design and implementation of scalable backend services that enable intelligent agents to automate complex equity workflows
• This is a 0-1 opportunity where you'll define service boundaries, design APIs, and build the distributed systems that make AI capabilities production-ready and reliable at scale
• In this high-impact role, you'll work directly with leadership to shape our technical strategy and establish architectural patterns that will guide our engineering organization as we scale
• 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