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Aaru

AI-driven multi-agent forecasting platform

Engineering Manager - Product

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • Strong product or full-stack engineering background, with the ability to work deeply in architecture, code, and debugging.
  • Experience leading a small engineering team that shipped and operated production products, preferably in a fast-moving or ambiguous environment.
  • Strong product judgment across customer evidence, interaction design, technical architecture, and organizational tradeoffs.
  • Ability to accelerate a team through clarity and effective systems rather than constant intervention or lowered standards.
  • Ability to distinguish compelling prototypes from products ready to support real customer decisions.
  • Ability to make crisp decisions with incomplete information, articulate assumptions, and change direction when evidence changes.
  • Ability to reduce complexity in product scope, architecture, code, process, and team ownership.
  • Ability to give clear feedback early, address performance problems promptly, and take responsibility for developing people.
  • Recruiting ability and capacity to explain a demanding mission, environment, and high performance bar.
  • Willingness to work in person in New York with a fast-moving team that resolves difficult questions directly.

Responsibilities

  • Build, lead, and develop a high-performing team of Product Engineers with clear ownership, strong technical judgment, and high product craft standards.
  • Set technical direction for the team's product domain across frontend, backend, application programming interfaces, data models, workflow orchestration, integrations, observability, and model-dependent behavior.
  • Partner with Product and Design to identify important user problems, define a coherent roadmap, and make principled scope and sequencing decisions.
  • Create an execution model for parallel workstreams with clear directly responsible individuals, credible milestones, early risk discovery, focused reviews, and rapid 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 difficult or ambiguous problems.
  • Turn specific customer evidence into generalizable product capabilities rather than custom branches, configuration debt, or manual operations.
  • Establish quality standards 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, explicitly address missing primitives, and contribute to shared foundations when appropriate.
  • Build feedback loops with Deployment and customers so 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 and 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.

Desired Qualifications

  • 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 rapid hiring while preserving talent density and technical culture.

About the Company

Aaru

AI-driven multi-agent forecasting platform

Aaru uses multi-agent simulations to forecast outcomes in political polling, business strategy, and global issue modeling. It builds virtual models of real-world actors, runs scalable cloud simulations, and uses machine learning to turn results into actionable forecasts. It differentiates itself by applying multi-agent forecasting to deliver more scenario testing at a lower cost than traditional polling, serving major policy groups and Fortune 500 companies. Its goal is to expand beyond elections to tackle a broader set of societal and business challenges with AI-driven analytics for decision-making.

Company size
51-200
Company stage
Series A
Total funding
$50M
Headquarters
New York City, New York
Founded
2024

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