ai engineer in quantitative trading

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. It develops AI systems and deploys them safely through its products.

• Work directly with quantitative investment and trading firms to identify opportunities across research, data analysis, and software development;
• Translate customer needs into practical implementations, evaluations, and measurable outcomes;
• Design, build, and deploy AI systems that solve important customer problems and produce measurable business outcomes;
• Build prototypes, evaluation harnesses, reference implementations, integrations, and production accelerators;
• Make technical decisions across models, agents, retrieval, tools, data, reliability, observability, latency, cost, safety, security, and governance;
• Diagnose complex implementation challenges, reproduce failures, test hypotheses, and drive blockers toward resolution;
• Help customers progress from prototypes to reliable production systems, sustained adoption, and scaled impact;
• Lead technical workshops and hands-on sessions for quantitative researchers and engineers;
• Bring quant customer needs into OpenAI’s product development through deployment experience, evaluations, and feedback;
• Create reusable architectures, tooling, playbooks, and technical guidance for future enterprise deployments.

• Experience in quantitative research, quantitative development, or a closely related role, or an excellent understanding of quantitative investment and trading teams;
• Practical, hands-on experience with LLMs, including tools such as Codex or AI applications;
• Substantial personal contributions in code, architecture, evaluation, debugging, or production engineering;
• High proficiency in Python;
• Experience building and debugging research tools, data workflows, or software systems;
• A rigorous approach to evaluating quantitative, statistical, or machine-learning systems;
• Experience with enterprise production requirements, including integrations, reliability, observability, security, privacy, data governance, performance, and cost;
• Ability to connect technical decisions to customer workflows, adoption, and measurable business outcomes;
• Clear and credible communication with engineers, technical leaders, security teams, product leaders, and executives;
• High agency, strong technical judgment, and end-to-end ownership in ambiguous environments;
• Ability to learn quickly, challenge assumptions constructively, and collaborate with humility.

• Relocation support is available.