Product Engineering Manager

Aaru•New York, NY

18h•Onsite

About The Position

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 Product Engineering Product Engineering turns Aaru's simulation capabilities into products that customers can use independently and repeatedly. The team builds on Aaru's shared platform and simulation systems to create the workflows, interfaces, integrations, and decision-ready artifacts that make a technically sophisticated system feel clear and dependable. The function is designed around durable product domains rather than a queue of disconnected features. Those domains may include simulation setup, question and experiment types, follow-up and continuous simulations, analysis and reporting, reusable customer templates, collaboration, and external integrations. Product Engineering is not a thin presentation layer and it is not a forward-deployed services team. It owns end-to-end product outcomes, while working through explicit interfaces with Platform Engineering, Simulation Engineering, Research, Product, Design, and Deployment. The role As Product Engineering Manager, you will lead a focused team of Product Engineers and be accountable for the quality, pace, and impact of what the team ships. Managers at Aaru remain builders. You will set technical direction, shape product decisions, review critical designs, write and debug code when it is the highest-leverage use of your time, hire exceptional engineers, and develop the people already on the team. You will partner closely with a Product Manager and Product Designer. Together, you will select problems, define the product domain, and establish a roadmap that balances immediate customer value with reusable product foundations. You will also create the operating mechanisms that let multiple workstreams move quickly without losing clarity, quality, or ownership. This is a line-management role, not a distant function-head role. Your primary responsibility is to make a small team unusually effective: give people context, set a high bar, resolve ambiguity, provide direct feedback, and ensure that commitments become excellent production systems.

Requirements

You were a strong product or full-stack engineer before becoming a manager and remain capable of going deep in architecture, code, and debugging.
You have led a small engineering team that shipped and operated meaningful production products, preferably in a fast-moving or ambiguous environment.
You have strong product judgment and can move between customer evidence, interaction design, technical architecture, and organizational tradeoffs.
You know how to make a team faster through clarity and better systems rather than through constant intervention or lowered standards.
You can separate a compelling prototype from a product that is ready to carry real customer decisions.
You make crisp decisions with incomplete information, state the assumptions behind them, and change direction when the evidence changes.
You reduce complexity in product scope, architecture, code, process, and team ownership.
You give clear feedback early, address performance problems promptly, and take genuine responsibility for developing people.
You recruit well and can explain a difficult mission, a demanding environment, and an unusually high bar without relying on title inflation.
You want to work in person in New York with a team that moves quickly and resolves hard questions directly.

Nice To Haves

Experience leading an AI-native product team, particularly one involving agents, model-dependent workflows, or probabilistic outputs.
Experience as a founder, founding engineer, or early engineering leader at a fast-growing startup.
Experience managing full-stack teams that work closely with Product and Design while depending on shared platform or infrastructure teams.
Experience with B2B or enterprise products involving integrations, permissions, auditability, complex configuration, or high-consequence workflows.
A record of turning customer-specific work into a durable product platform or reusable set of primitives.
Experience partnering with research or machine-learning teams and creating a disciplined path from experimental capability to production product.
Experience building teams through a period of rapid hiring while preserving talent density and technical culture.

Responsibilities

Build, lead, and develop a high-performing team of Product Engineers with clear ownership, strong technical judgment, and a high standard for product craft.
Set technical direction for the team's product domain across frontend, backend, APIs, data models, workflow orchestration, integrations, observability, and model-dependent behavior.
Partner with Product and Design to identify the most important user problems, define a coherent roadmap, and make principled decisions about scope and sequence.
Create an execution model for parallel workstreams: clear DRIs, credible milestones, early risk discovery, focused reviews, and fast escalation when dependencies or assumptions fail.
Stay close to the work through system design, architecture reviews, code review, debugging, product critique, user sessions, and direct contribution to the hardest or most ambiguous problems.
Ensure that the team turns specific customer evidence into generalizable product capabilities rather than accumulating custom branches, configuration debt, or manual operations.
Establish a quality bar for AI-native product development, including evaluations, human review points, instrumentation, rollout criteria, fallbacks, provenance, and safe rollback.
Define clean interfaces with Platform Engineering and Simulation Engineering.
Work through missing primitives explicitly and contribute to shared foundations when that is the right organizational answer.
Build tight feedback loops with Deployment and customers so that field failures, confusing workflows, and unexpected model behavior become prioritized product and engineering work.
Own production quality for the team's systems, including reliability, latency, security, permissions, cost, on-call health, incident follow-up, and maintenance.
Recruit exceptional engineers from sourcing through close.
Build a team with the right mix of product sense, technical depth, speed, and ownership.
Set expectations clearly, provide frequent and candid feedback, recognize exceptional work, address performance problems early, and invest in each engineer's growth.
Improve the broader engineering organization through reusable patterns, stronger development tools, better technical communication, and a culture of thoughtful urgency.