Founding Infrastructure Engineer (Real-Time Systems) (Equity-Based – Pre-Funding Startup)

Orchestrator is building an autonomous intelligence layer that enables continuous reasoning, predictive decision-making, and real-time execution inside enterprise workflows. They are seeking a Founding Infrastructure Engineer to design, build, and manage the real-time systems that power their trading decision intelligence platform, TraderClear.

Responsibilities:

• Design and manage cloud infrastructure for real-time, high-frequency data systems
• Build and maintain pipelines for: market data ingestion (price, volume, streaming data)
• Broker API integrations (executions, orders, positions)
• Architect systems to automatically capture and store trading activity with full context
• Develop event-driven pipelines for: trade execution events, market condition changes and real-time system triggers
• Build scalable infrastructure for time-series and high-throughput data processing
• Optimize systems for low latency and high concurrency where delays impact outcomes
• Implement monitoring, logging, and reliability frameworks focused on: data accuracy, system performance and pipeline integrity
• Handle data normalization across fragmented external systems (brokers, APIs, feeds)
• Ensure scalability, fault tolerance, and uptime in always-on, real-time environments
• Support infrastructure for continuous processing systems, not batch-based workflows

Requirements:

• Experience with cloud infrastructure, deployment pipelines, and production systems
• Experience working with real-time data streaming systems (WebSockets, Kafka, Pub/Sub, etc.)
• Familiarity with time-series data and high-frequency data pipelines
• Experience integrating with external APIs at scale
• Strong understanding of event-driven architecture and asynchronous systems
• Experience with monitoring, logging, and reliability practices
• Ability to work in an early-stage environment with high autonomy
• Strong systems thinking and comfort with ambiguity
• Exposure to trading systems, financial data infrastructure, or market data environments
• Experience handling low-latency systems and performance optimization
• Experience normalizing data across multiple inconsistent sources