Full Stack AI Engineer (Fully Remote)

Reveleer; United States; A distancia; USD 120.000 - 180.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Medical, Dental, and Vision benefits

Generous PTO plan

Descripción de la vacante

Reveleer is a value-based care technology platform that unifies retrieval, clinical intelligence, risk adjustment, quality improvement, and member management into one AI-powered system. The company is a small but impactful team within the AI division, focused on developing next-generation agentic models for clinical prospective suspecting.

We are seeking engineers who apply first-principles thinking to break down hard problems, build end-to-end product experiences across the stack, and

Formación

• Experience applying first-principles thinking to complex problems.
• Ability to design end-to-end product experiences across the stack.
• Experience collaborating with clinical experts and engineers.

Responsabilidades

• Apply first-principles thinking to break down hard problems and ship durable solutions.
• Understand business needs and build end-to-end product experiences across the stack.
• Partner closely with clinical experts and other engineers to build scalable, clinically accurate systems.

Conocimientos

First-principles thinking

End-to-end product experience

Collaboration with clinical experts

Descripción del empleo

• Apply first-principles thinking to break down hard problems and ship durable solutions.
• Understand business needs and build end-to-end product experiences across the stack.
• Partner closely with clinical experts and other engineers to build scalable, clinically accurate systems.

What You'll Receive:

• Medical, Dental, and Vision benefits.
• Generous PTO plan.

Reveleer is a value-based care technology platform that unifies retrieval, clinical intelligence, risk adjustment, quality improvement, and member management into one AI-powered system. The company is a small but impactful team within the AI division, focused on developing next-generation agentic models for clinical prospective suspecting.