You will build the Agentic Architecture- the distributed systems, task-orchestration layers, and real-time execution environments that allow AI agents to perceive the market and act autonomously
What you'll do
Architect Agentic Service Infrastructure: Design and scale the high-concurrency backend services and distributed systems that power our AI agents' real-time decision-making.
Build the RAG & Execution Engine: Engineer the backend services for vector search, context-aware retrieval, and the "memory" layers required for agentic workflows.
Develop High-Performance Extraction Systems: Build resilient, distributed crawling and scraping services that function as the "sensory" input for our engine.
System Orchestration: Manage the integration of LLMs and predictive models into the core product API, ensuring low-latency execution and high system reliability.
Define Engineering Excellence: Establish backend architectural patterns, coding standards, and service-oriented best practices for the entire engineering team.
8+ years of experience: Deep expertise in Backend Engineering with a software-first approach to complex systems.
AI-Native Workflow: You have a significant advantage if you leverage modern, agentic development environments like Claude Code to accelerate system design and iteration.
The Tech Stack: Strong proficiency in building scalable services. While we value architectural skill over specific syntax, experience with Go (Golang) and GCP (BigQuery/Cloud Run/Postgres) is a major "force multiplier" for our stack.
Agentic Systems Knowledge: Familiarity with the infrastructure needed for LLMs, Vector Databases, and RAG-based application logic.
Architectural Ownership: You excel at taking a high-level business need and designing the full-stack service architecture required to solve it.
