Senior Applied AI Engineer — Greenfield Systems

Cyrad Solutions LLC; New York (NY); Presencial; USD 400.000 - 1.000.000; Jornada completa

Descripción de la vacante

Cyrad Solutions LLC is hiring an engineer to define and build the first generation of AI systems for a technically demanding, research-driven environment in New York. You will own greenfield work end-to-end with significant autonomy and tangible organizational impact.

The role focuses on production AI agents, frameworks, and platforms, requiring hands-on experience with LLMs and agentic architectures. Exceptional candidates may see flexibility above the stated compensation for top performance.

Formación

• Experience with large language models and AI agents in production
• Track record of building sophisticated software systems
• Ability to reason from first principles in ambiguous environments
• Demonstrated academic, technical, or professional excellence

Responsabilidades

• Design and ship production AI agents spanning orchestration, tool use, memory, retrieval, and multi-step reasoning
• Own greenfield projects from concept through deployment and scale
• Build coding agents and developer tools that change how software is written
• Develop reusable agent frameworks and internal AI platforms
• Rapidly evaluate emerging models and techniques and turn strong ideas into production systems
• Handle technically ambitious problems with no established playbooks

Conocimientos

Software engineering

LLMs & AI agents

Production AI systems

First-principles reasoning

Ambiguity tolerance

Herramientas

Agent frameworks

Memory systems

Retrieval systems

AI infrastructure

Descripción del empleo

Cyrad Solutions LLC is hiring an engineer to define and build the first generation of AI systems for a technically demanding, research-driven environment in New York. You will own greenfield work end-to-end with significant autonomy and tangible organizational impact.

The role focuses on production AI agents, frameworks, and platforms, requiring hands-on experience with LLMs and agentic architectures. Exceptional candidates may see flexibility above the stated compensation for top performance.