Founding Software Engineer
- $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.