Engineer, Infrastructure

Aaru•New York, NY

1d•$250,000 - $800,000•Onsite

About The Position

Aaru is a predictive-intelligence company that uses AI agents to simulate human behavior and help organizations anticipate outcomes. The company describes itself as a small, mission-driven team that values ownership, trust, urgency, intellectual honesty, curiosity, and impactful work. The Infrastructure Engineer will build systems that enable Aaru’s simulations to run faster, more reliably, and at greater scale. The role spans compute, networking, data pipelines, and developer tooling, with the goal of removing bottlenecks from core engineering and research workflows. The position is based in New York City and is in-office five days a week; candidates should be in the New York City metropolitan area or willing to relocate.

Requirements

Experience building infrastructure, frameworks, or internal platforms for fast-growing engineering teams.
Deep experience debugging performance and reliability issues in distributed systems.
Comfort working close to networking, storage, compute, and cloud primitives.
Experience helping transition research or experimental systems into production.
Care about developer experience and building systems that other engineers want to use.
Comfort with strongly typed languages or languages with algebraic type systems.

Nice To Haves

Experience with long-running computational pipelines.
Strong knowledge of networking protocols such as HTTP, TLS, TCP, or related systems.
Experience designing infrastructure for high-scale data or machine learning workloads.
A track record of finding and eliminating bottlenecks in complex systems.

Responsibilities

Design and build low-latency, high-throughput infrastructure for large-scale simulations.
Improve the reliability and performance of data ingestion and computation pipelines.
Identify system bottlenecks across compute, networking, storage, and orchestration.
Build tools and abstractions that help engineering and research teams move faster.
Productionize experimental research workflows into reliable, repeatable infrastructure.
Own infrastructure decisions from architecture through implementation and operation.