Founding Member of Technical Staff — Markets

Recruiting From Scratch • Palo Alto, CA

12d • Onsite

About The Position

Join a seed-stage AI and financial technology company building an AI-powered prediction engine for financial and prediction markets. The technology combines reasoning systems with information from social media, online communities, and prediction markets to produce trading insights and signals. The company’s research and trading technology is already used in a live trading operation, and the team works across engineering, quantitative research, AI research, and trading.

This founding-level engineering role involves taking projects from initial exploration and design through implementation, testing, deployment, and production operation. The engineer will build and operate systems across the trading stack, including market-data processing, data pipelines, research infrastructure, trading signals, automated execution, machine-learning infrastructure, and security. The role calls for strong engineering fundamentals, ownership, curiosity about markets, and comfort working through ambiguous problems on a small team with limited process.

The position is on-site in Palo Alto six days per week. Compensation is a base salary of $200,000–$300,000, competitive equity, and discretionary performance bonuses based on individual contribution. The company is open to eligible visa transfers and new sponsorship, subject to individual eligibility.

Requirements

• 1–5 years of full-time professional experience as a software engineer or quantitative developer.
• Strong software engineering fundamentals and ability to build production-quality systems.
• Strong programming experience in Python and/or C++.
• Ability to own projects from an initial idea through implementation and production.
• Strong problem-solving skills and ability to reason through ambiguous technical challenges.
• Genuine curiosity about financial markets, trading, market behavior, or quantitative research.
• Interest in building systems that connect research, data, and automated execution.
• Comfort working on a small, high-performance team with broad responsibilities and limited process.
• Ability to collaborate with quantitative researchers, AI researchers, and other engineers.
• Willingness to work on-site in Palo Alto six days per week.
• Ability to write clean, maintainable, reliable code and take ownership of implementation decisions.

Nice To Haves

• C++ experience with performance-sensitive systems, trading infrastructure, or technically demanding applications.
• Experience ingesting, processing, and transforming structured or unstructured data.
• Experience building backend services, internal tools, or systems supporting production applications.
• Familiarity with trading infrastructure, market data, execution systems, or financial applications.
• Experience supporting quantitative research, strategy development, backtesting, or experimentation.
• Experience building research tools that help evaluate hypotheses and iterate quickly.
• Awareness of system performance, correctness, failure handling, and production reliability.
• Familiarity with AI systems, reasoning models, or machine-learning infrastructure.
• Experience at a quantitative trading firm, hedge fund, market-making firm, or other trading-focused organization.
• Experience developing automated trading systems or market-data infrastructure.
• Experience with high-frequency trading systems or latency-sensitive applications.
• Experience building quantitative research tools, backtesting infrastructure, or strategy-evaluation systems.
• Experience working with real-time data, alternative data, or large-scale data ingestion.
• Experience collaborating with quantitative or machine-learning researchers.
• Experience moving research prototypes into production.
• Familiarity with prediction markets, financial markets, or algorithmic trading.
• Experience at a technically demanding startup or small engineering team.
• Strong academic, competitive-programming, mathematical, or quantitative achievements.

Responsibilities

• Own projects end-to-end, from exploration and design through implementation, testing, deployment, and production operation.
• Build and extend infrastructure for research, market-data processing, trading signals, and automated execution.
• Develop pipelines to ingest and process market data, alternative data, social media information, and other relevant sources.
• Create research tools and systems that help quantitative and AI researchers test hypotheses, evaluate strategies, and run live experiments.
• Build software and tooling that translate research ideas into reliable production trading systems.
• Improve infrastructure and workflows to accelerate experimentation and evaluation of market predictions.
• Collaborate with quantitative and AI researchers to turn market-prediction approaches into working software.
• Contribute across data infrastructure, trading systems, research tooling, high-performance systems, machine-learning infrastructure, and security.
• Assess ambiguous problems, identify practical solutions, and develop systems when existing tools or approaches are insufficient.
• Take responsibility for the performance, reliability, and correctness of systems in production.
• Contribute to architectural decisions and engineering practices as the team develops its technology.
• Move quickly while maintaining the engineering discipline needed for systems connected to live trading operations.

Benefits

• Competitive equity, with generous grants for strong candidates.
• Discretionary performance bonuses based on individual contribution.
• Opportunity to take founding-level ownership at an early-stage company.
• Direct collaboration with experienced engineers, quantitative researchers, AI researchers, and traders.
• Opportunity to build production systems supporting a live trading operation.
• Broad technical exposure across data infrastructure, research tooling, trading systems, and automated execution.
• Significant individual ownership on a small, technically strong team. The posting also describes meaningful responsibility, direct impact, and opportunities to shape the team’s technical direction.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed