Product Engineer: AI Simulations (In-Person NYC)

Aaru

New York (NY)

On-site

USD 140,000 - 170,000

Full time

14 days+
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Benefits offered by this job

Competitive base salary
Equity participation
Medical, vision, and dental coverage
Visa sponsorship
Relocation support

Job summary

Aaru in New York City builds simulations of human behavior and delivers decision-ready products for customers. As a Product Engineer, you will take ambiguous user problems from first conversations to reliable product capability, working with Product, Design, Deployment, Platform Engineering, Simulation Engineering, and Research.

You will prototype quickly but ship robust, observable systems that are maintainable, secure, and scalable, with a focus on user outcomes across the stack and strong

Qualifications

  • Proven experience turning ambiguous user problems into durable product features.
  • Ability to design across frontend, backend, and data models.
  • Strong collaboration with design, deployment, and research teams.
  • Comfort with AI-native product considerations and graceful failure modes.

Responsibilities

  • Own product work end to end from problem to production.
  • Observe real decision workflows with users and teams.
  • Build polished experiences across frontend, backend, APIs, and data models.
  • Design product behavior amidst AI uncertainty and provide clear states.

Skills

Software engineering fundamentals
Frontend & Backend
APIs
Data modeling
Workflow orchestration

Tools

TypeScript
React
Python
APIs
Workflow systems
Cloud infrastructure

Job description

Aaru in New York City builds simulations of human behavior and delivers decision-ready products for customers. As a Product Engineer, you will take ambiguous user problems from first conversations to reliable product capability, working with Product, Design, Deployment, Platform Engineering, Simulation Engineering, and Research.

You will prototype quickly but ship robust, observable systems that are maintainable, secure, and scalable, with a focus on user outcomes across the stack and strong

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