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AA
Aaru

Engineering Manager, Product

LocationNYC
Work modeon-site
Typefull-time
DepartmentTechnical Staff
Company size11+ people
First seen2w ago
Last seen1d ago
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 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.
What you will do
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Build, lead, and develop a high-performing team of Product Engineers with clear ownership, strong technical judgment, and a high standard for product craft.
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Set technical direction for the team’s product domain across frontend, backend, APIs, data models, workflow orchestration, integrations, observability, and model-dependent behavior.
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Partner with Product and Design to identify the most important user problems, define a coherent roadmap, and make principled decisions about scope and sequence.
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Create an execution model for parallel workstreams: clear DRIs, credible milestones, early risk discovery, focused reviews, and fast escalation when dependencies or assumptions fail.
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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.
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Ensure that the team turns specific customer evidence into generalizable product capabilities rather than accumulating custom branches, configuration debt, or manual operations.
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Establish a quality bar for AI-native product development, including evaluations, human review points, instrumentation, rollout criteria, fallbacks, provenance, and safe rollback.
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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.
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Build tight feedback loops with Deployment and customers so that field failures, confusing workflows, and unexpected model behavior become prioritized product and engineering work.
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Own production quality for the team’s systems, including reliability, latency, security, permissions, cost, on-call health, incident follow-up, and maintenance.
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Recruit exceptional engineers from sourcing through close. Build a team with the right mix of product sense, technical depth, speed, and ownership.
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Set expectations clearly, provide frequent and candid feedback, recognize exceptional work, address performance problems early, and invest in each engineer’s growth.
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Improve the broader engineering organization through reusable patterns, stronger development tools, better technical communication, and a culture of thoughtful urgency.
Representative leadership problems
You might be responsible for situations such as:
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The team has five credible feature opportunities but only enough capacity to pursue two. Determine which problems matter, what evidence would change the decision, and how to sequence the work without creating strategic drift.
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A major customer request is valuable but highly specific. Find the underlying general problem and design a capability that serves the customer without turning the product into consulting software.
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A new research capability produces impressive demonstrations but inconsistent user outcomes. Define the evaluations, interaction design, constraints, and rollout plan required before it becomes a product feature.
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Product delivery is repeatedly blocked by missing platform primitives. Decide what belongs in Product Engineering, what belongs in Platform, and whether temporary embedding or shared ownership is the fastest durable path.
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Two workstreams are moving quickly but making incompatible architectural choices. Establish the shared contract before the divergence becomes expensive.
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A workflow is technically correct but users do not trust it. Diagnose whether the issue is product framing, interaction design, provenance, latency, model behavior, or actual quality—and direct the team toward evidence rather than opinion.
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The team is shipping rapidly but support burden and incident frequency are rising. Restore operational discipline without replacing ownership with bureaucracy.
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A strong engineer is producing excellent individual work but is not creating leverage for teammates. Give direct feedback, define the next level of impact, and support the behavior change.
How we work
We begin with the decision the user is trying to make, not with a feature request. We seek direct evidence, reduce the problem to its essential uncertainty, and build the smallest system that can resolve it. We move quickly, but we preserve the foundations required for reuse and long-term ownership.
For AI-native products, product quality and model quality are inseparable. Latency, interaction design, evaluation, orchestration, permissions, reliability, and the behavior of the underlying models all shape the user experience. The manager must create a team that can reason across these layers without losing accountability at the boundaries.
Management at Aaru is an active technical discipline. The goal is not to become the routing layer for every decision. The goal is to give strong people enough context, clarity, and feedback that they can own increasingly difficult decisions themselves.
You might thrive in this role if
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You were a strong product or full-stack engineer before becoming a manager and remain capable of going deep in architecture, code, and debugging.
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You have led a small engineering team that shipped and operated meaningful production products, preferably in a fast-moving or ambiguous environment.
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You have strong product judgment and can move between customer evidence, interaction design, technical architecture, and organizational tradeoffs.
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You know how to make a team faster through clarity and better systems rather than through constant intervention or lowered standards.
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You can separate a compelling prototype from a product that is ready to carry real customer decisions.
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You make crisp decisions with incomplete information, state the assumptions behind them, and change direction when the evidence changes.
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You reduce complexity in product scope, architecture, code, process, and team ownership.
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You give clear feedback early, address performance problems promptly, and take genuine responsibility for developing people.
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You recruit well and can explain a difficult mission, a demanding environment, and an unusually high bar without relying on title inflation.
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You want to work in person in New York with a team that moves quickly and resolves hard questions directly.
Strong candidates may also have
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Experience leading an AI-native product team, particularly one involving agents, model-dependent workflows, or probabilistic outputs.
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Experience as a founder, founding engineer, or early engineering leader at a fast-growing startup.
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Experience managing full-stack teams that work closely with Product and Design while depending on shared platform or infrastructure teams.
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Experience with B2B or enterprise products involving integrations, permissions, auditability, complex configuration, or high-consequence workflows.
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A record of turning customer-specific work into a durable product platform or reusable set of primitives.
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Experience partnering with research or machine-learning teams and creating a disciplined path from experimental capability to production product.
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Experience building teams through a period of rapid hiring while preserving talent density and technical culture.
Candidates need not have
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Prior experience in simulation or computational social science.
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Managed managers or a large organization; this role is about leading one focused team exceptionally well.
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Experience with every layer of Aaru’s stack. We care about technical depth, product judgment, and the ability to learn enough to make sound decisions.
What success looks like
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The team has a clear product domain, a credible roadmap, and explicit ownership that lets multiple workstreams move in parallel.
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Product Engineers operate with high autonomy because goals, interfaces, quality bars, and decision rights are clear.
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The team ships products that customers adopt and trust—not merely features that satisfy an internal specification.
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Customer-specific evidence repeatedly becomes reusable capability, while one-off work and manual support decrease.
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Model behavior, product quality, latency, reliability, cost, and adoption are observable and used in day-to-day decisions.
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Platform, Simulation Engineering, Research, Product, Design, and Deployment experience the team as a clear, dependable partner with well-defined interfaces.
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Strong engineers join, grow, and do the best work of their careers; performance issues are handled directly and fairly.
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The team moves quickly without sacrificing production ownership, product craft, or the long-term coherence of the system.
Location and benefits
This role is based in New York City. Aaru is an in-person company, working five days a week in the office. Candidates should be located in the New York metropolitan area or open to relocation.
Aaru offers a competitive base salary, equity participation, comprehensive medical, vision, and dental coverage, visa sponsorship and relocation support, and other benefits and perks. Final compensation depends on level and experience and is set within Aaru’s internal bands.
More roles at Aaru
Engineer, InfrastructureSales DirectorSimulation Architect, WestDeployment Lead, AlliancesProduct Manager, Artifacts
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