Founding Software Engineer

LB39
  • $200,000 - $250,000
  • California, United States
  • Permanent

Founding Software Engineer 


💰 $200,000–$250,000 with equity


The Opportunity

Join a very early-stage applied-AI company building an AI research analyst—and, ultimately, an AI-native investor for financial markets.

The platform turns high-level investment questions into repeatable workflows: decomposing them into tasks, writing and executing auditable data-science code, evaluating results, and presenting findings investors can inspect and reuse.

The central challenge is building a system that becomes more intelligent, reliable, and useful over time.


The Role

As a Founding Software Engineer, you will work across the Python backend, agent orchestration, evaluation, traceability, data infrastructure, code execution, and output quality.

This is a hands-on role for a high-intelligence, high-agency Python generalist—not a conventional backend position with narrow boundaries. You will identify where the system fails and improve it end to end.


What You’ll Do

  • Build a production-grade Python platform for AI-driven investment research
  • Design agents that break complex questions into effective research tasks
  • Develop systems for generating and safely executing auditable data-science code
  • Evaluate reasoning quality, reliability, and usefulness
  • Make the system’s conclusions and processes traceable
  • Diagnose failures across decomposition, reasoning, tool use, and code execution
  • Build the supporting backend and data infrastructure
  • Turn ambiguous problems into reliable production systems
  • Help shape the architecture, product, and engineering culture


What We’re Looking For

  • Exceptional Python engineering ability
  • High intellectual horsepower, agency, and learning speed
  • Experience building substantial applied-AI, research-engineering, or backend systems
  • Evidence of taking ambiguous projects from concept to production
  • Strong judgment across software architecture, data systems, and product quality
  • Comfort investigating complex failures rather than treating AI behavior as a black box
  • A bias toward building, measuring, and iterating
  • Interest in AI systems, financial research, or machine-assisted decision-making


Relevant experience:

  • LLM agents, orchestration frameworks, or tool-using systems
  • Model evaluation and quality-measurement infrastructure
  • Secure or sandboxed code execution
  • Data-science or quantitative-research workflows
  • Financial data platforms
  • Observability, provenance, or auditability


Why Join?

🚀 Join early enough to shape both the intelligence system and the company.

  • You will have broad ownership, direct founder access, and the opportunity to solve difficult problems at the intersection of applied AI, data science, and financial markets.
Samuel Killick Researcher

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