The opportunity
OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. We work with customer executives, product and engineering teams, security leaders, and transformation teams to identify valuable…
What you'll do
Work directly with quantitative investment and trading firms to identify: opportunities across research, data analysis and software development, translating their needs into practical implementations, evaluations and measurable outcomes.
Design, build, and deploy AI systems that solve important customer problems: and produce measurable business outcomes.
Work hands-on in code to build prototypes, evaluation harnesses, reference: implementations, integrations, and production accelerators.
Make sound 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 promising prototypes to reliable production: systems, sustained adoption, and scaled impact.
What they're looking for
- Lead technical workshops and hands-on sessions that help quantitative: researchers and engineers apply OpenAI’s models and Codex effectively in their day-to-day work.
- Bring the needs of quant customers into OpenAI’s product development,: translating deployment experience, evaluations and feedback into clear requirements for Product, Research and Engineering.
- Create reusable architectures, tooling, playbooks, and technical guidance: that accelerate future enterprise deployments.
- Have worked in quantitative research, quantitative development or a closely: related role, or can demonstrate an excellent understanding of how quantitative investment and trading teams operate. You understand their research processes, technical environments and expectations for rigorous evaluation.
