Software Engineer, Applied Ai

Aaru•New York, NY

19h•$250,000 - $325,000•Onsite

About The Position

The Applied AI team works across the stack to improve Aaru's simulation pipelines and explore new product areas where simulations can be useful. The work can range from infrastructure and platform systems to frontend experiences and APIs. It is organized around the highest-leverage initiatives the company is pursuing, rather than a fixed technical domain. Applied AI Engineers own outcomes across the stack and work cross-functionally with other engineering teams and GTM teams such as Deployment to ensure that what we build becomes a strong product and developer experience. As an Applied AI Engineer, you will work on high-leverage initiatives at the intersection of AI systems, simulation infrastructure, and product development. You will improve existing capabilities, help prototype and evaluate promising company bets, and turn experimental ideas into reliable systems. The work is initiative-driven rather than defined by a fixed product roadmap or a single layer of the stack. You will work primarily in Python and TypeScript, but you will use whatever technologies are necessary to finish the job. You will move from an ambiguous problem to a working system: understand the problem, find the smallest useful experiment, improve the architecture, evaluate the result, deploy it, and continue iterating based on evidence. This is a role for a strong general software engineer who wants to work in an AI-native environment. Prior experience with AI or agent systems is helpful, but the more important qualities are sound engineering judgment, curiosity, and the ability to learn quickly across unfamiliar parts of a system.

Requirements

Comfortable with loosely specified problems and can turn ambiguity into a useful next step.
Strong general software engineering fundamentals and can work across layers when the problem requires it.
Enjoy fast iteration and are willing to change direction when evidence points somewhere else.
Care about testability, evaluation, performance, maintainability, and the difference between a demo and a dependable system.
Take responsibility for outcomes through implementation, deployment, measurement, and iteration.
Communicate directly, work well across functions, and make technical tradeoffs clear to people with different backgrounds.
Want to build AI-native systems whose impact is not bounded by a single technical domain.

Nice To Haves

Experience building AI-native products, agents, LLM applications, or other systems in which model behavior materially shaped the user experience.
Experience building evaluation tools, test harnesses, reproducible fixtures, or systems for detecting regressions in complex behavior.
Experience improving throughput, performance, or reliability in data, compute, or workflow pipelines.
Experience working at an early-stage company or on projects where you owned a broad problem from initial idea through production.
Fluency with technologies such as Python, TypeScript, React, APIs, workflow systems, relational data models, and cloud infrastructure—or equivalent depth in a comparable stack.

Responsibilities

Improve agent functionality within Aaru's product, including interaction design, tool use, context handling, orchestration, reliability, and model behavior.
Optimize simulation pipelines to increase throughput, remove bottlenecks, and make large or repeated runs more efficient.
Build evaluation harnesses and supporting architecture that make agent and simulation capabilities testable, reproducible, and easier to improve.
Help prototype and evaluate promising company bets through focused experiments and technical investigations, then help build out the ideas that merit further investment.
Work cross-functionally with other engineering teams and GTM teams such as Deployment to make new capabilities usable, supportable, and dependable in real workflows.
Write clear technical designs and documentation. Make assumptions, dependencies, tradeoffs, and unresolved risks legible to the rest of the organization.