Applied AI Engineer

Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria.

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.

Can point to substantial personal contributions in code, architecture, evaluation, debugging, or production engineering—not only program or stakeholder management.

Are highly proficient in Python and comfortable working across an AI application stack; experience with JavaScript, TypeScript, or another relevant language is valuable.

Understand how to evaluate AI systems systematically using representative data, graders, production signals, and human judgment.

Have navigated enterprise production requirements such as integrations, reliability, observability, security, privacy, data governance, performance, and cost.