Simulation Engineering Manager

About the company

Aaru provides near-instant customer research by using AI agents to simulate human behavior and predict market responses.

About this role

ABOUT AARU Aaru builds simulations of human behavior. Each simulation contains a population of AI agents, each representing a person who could plausibly exist in the real world and capable of making decisions within a modeled environment. Companies and institutions use these simulations to test consequential choices before committing—from product launches and pricing decisions to strategic communications and policy changes. Building a useful simulation requires more than generating plausible text. Populations must represent real people and groups; predictions must be calibrated; simulations must remain coherent as conditions change; and the product must make the resulting evidence legible enough to support real decisions. We are a small, in-person team in New York. We work with urgency, high ownership, and intellectual honesty. We expect people to surface inconvenient evidence, change their minds quickly, and carry important work all the way to a result. ABOUT SIMULATION ENGINEERING Simulation Engineering owns the path from a promising research result to a production system that customers can trust. Researchers may prove a new method for constructing a population, modeling a world, estimating an outcome, or evaluating fidelity. Simulation Engineering turns that method into robust, reusable, observable, and efficient software. The team's quality bar is broader than conventional service reliability. A production simulation must be behaviorally faithful, calibrated, reproducible, measurable, fast enough to use, economical enough to scale, and reliable under real customer workloads. The team owns the abstractions, contracts, evaluation gates, workflows, and operating systems that make those properties possible. Simulation Engineering is not a research-support queue. It is the engineering owner of the simulation system in production. When a simulation method breaks, regresses, becomes too expensive, or produces conclusions that cannot be explained, this team is accountable for finding the cause and restoring trust. THE ROLE As Simulation Engineering Manager, you will lead a focused team of Simulation Engineers and be accountable for the quality, pace, and operational health of Aaru's production simulation system. Managers at Aaru remain engineers. You will set technical direction, review critical designs, write and debug code when needed, inspect model and system failures, hire exceptional engineers, and develop the people on the team. You will operate at the interface of Simulation Research, Population Research, Prediction Research, Evaluation Research, Product Engineering, Platform Engineering, Infrastructure, and Deployment. A major part of the job is establishing explicit handoffs and shared evidence: what a research result must demonstrate before productionization, what the production system must expose for evaluation, and how field failures return to the right research or engineering owner. This is a line-management role. You are responsible for making one team exceptionally effective, not for building a layer of managers beneath you. You should expect to remain close to architecture, code, experiments, incidents, and the hardest technical tradeoffs. WHAT YOU WILL DO - Build, lead, and develop a high-performing team of Simulation Engineers with clear ownership of production simulation quality. - Own quality across behavioral fidelity, calibration, reproducibility, latency, throughput, cost, reliability, debuggability, and safe operation. - Define the architecture and operating model that carries a method from research prototype through evaluation, integration, rollout, observation, and continuous improvement. - Establish clear readiness criteria with Research and Evaluation: strong baselines, decisive experiments, protected holdouts, known limitations, and evidence that survives changes in domain, population, and time. - Design and maintain the core abstractions of the simulation system, including agent and population representations, simulation contracts, environment and state models, workflow boundaries, evaluation interfaces, and publication layers. - Build evaluation harnesses, benchmarks, ablations, graders, regression suites, and launch scorecards that distinguish a faithful simulation from a merely plausible output. - Make large simulation runs reproducible and inspectable by versioning models, prompts, data, populations, environments, code, and experiment configuration. - Build observability that connects system behavior to model behavior: traces, intermediate artifacts, cohort diagnostics, cost and latency curves, failure classification, and comparison across versions. - Set technical direction for scaling large population runs without concealing uncertainty or trading away the fidelity that makes the simulation useful. - Partner with Product Engineering to adapt the simulation system for new product goals while preserving valid contracts and avoiding product-specific forks in the core engine. - Build fast feedback loops with Deployment. Convert field failures, surprising customer outcomes, and operational incidents into concrete hypotheses, durable tests, fixes, and research questions. - Own the team's production operations, including on-call health, incident response, release safety, rollback, maintenance, and the elimination of recurring operational toil. - Recruit exceptional engineers, provide direct feedback, develop technical leaders, and address performance or ownership gaps early. - Improve engineering practice across Aaru by raising the bar for experimental discipline, production code, technical design, reproducibility, and post-incident learning. REPRESENTATIVE LEADERSHIP PROBLEMS You might be responsible for situations such as: - A new method improves an offline benchmark but changes customer conclusions unpredictably. Determine whether the issue is contamination, objective mismatch, population shift, nondeterminism, o