Jobs at Aaru

Build and operate infrastructure for large-scale simulations, focusing on low-latency systems, data and computation pipelines, distributed-system reliability, networking, storage, orchestration, developer tooling, and productionizing research workflows. Own infrastructure architecture through implementation and operations while eliminating bottlenecks and improving engineering and research productivity.

Own company-wide infrastructure security, establish the security roadmap, and implement controls across cloud infrastructure, identity and access management, autonomous agents, software delivery, supply chain, and employee devices. Build monitoring, detection, incident response, threat modeling, and architecture review practices while partnering with engineering, research, and compliance teams to manage risk and maintain practical, auditable controls.

Design and deliver brand work across web, social, presentations, print, product, and other customer-facing surfaces. Build scalable brand systems, lead launches and campaigns, partner with product designers and design engineers, enable teams to create on-brand materials, and manage external agencies when needed. The role requires strong visual judgment, clear communication, comfort with ambiguity, rapid execution, and the ability to use AI tools while maintaining independent creative taste.

Design Engineer who collaborates with product and brand designers, platform engineers, and product managers to build polished product experiences in code. Responsibilities include exploring interfaces, implementing visual identity, shaping solutions around user needs and technical constraints, and advancing the shared design system. The role requires front-end coding ability, strong interaction and visual design judgment, clear communication, and comfort working in ambiguous, fast-moving environments.

Own end-to-end engagements with law firms, translating litigation strategy into AI simulations, delivering findings to senior legal leaders, and developing long-term client relationships. Present recommendations, coordinate with engineering, product, and commercial teams, identify new opportunities, and support law firm brand and go-to-market strategy. The role requires a former or current complex litigator interested in applying predictive technology to litigation and regulatory strategy.

Build and lead Aaru’s enterprise sales organization, recruit and coach Account Executives, own revenue targets, and establish repeatable sales motions. Engage C-suite and government decision-makers, manage complex enterprise procurement, oversee forecasting and pipeline discipline, and partner with AI, product, marketing, legal, and deployment teams to drive customer adoption and expansion.

Lead the Artifacts product roadmap for AI-generated deliverables, including executive summaries, insight-generating documents, and interactive experiences. Collaborate with engineering, design, research, customers, and partners to establish evaluation and launch criteria, convert custom deliverables into reusable templates, debug model reasoning failures, identify platform gaps, measure adoption, trust, and quality, and present product strategy to executives.

Own strategic alliance and client relationships from discovery through deployment and expansion. Lead complex AI simulation engagements, joint selling, proposals, partner enablement, Centers of Excellence, governance, playbooks, and repeatable go-to-market systems. Collaborate with engineering, product, deployment, and commercial teams to translate partner needs into scalable solutions. Represent the company with senior executives and help partners embed the technology across their organizations and client offerings.

Serve as the technical bridge in pre-sales: lead technical discovery, design simulation-based POCs and demos, partner with commercial teams, support delivery handoff, relay client feedback to product/engineering, and communicate data-heavy findings to stakeholders.

Lead a focused team researching empirical prediction systems, including calibration, forecasting, subgroup performance, drift, and agentic prediction. Set research priorities, design rigorous experiments, build models from heterogeneous real-world data, and establish standards for temporal validity and prospective evaluation. Manage researchers, recruit and mentor talent, communicate evidence clearly, and transfer validated methods into production through cross-functional partnerships with population, evaluation, engineering, data, and product teams.

Lead Aaru’s Simulation Engineering team and own the quality, scalability, reproducibility, observability, and operational health of production AI simulations. Set architecture and productionization standards, build evaluation and regression systems, improve large-scale simulation performance, manage incidents and releases, collaborate across research and engineering, and recruit and develop high-performing engineers. The role remains hands-on, involving technical design, coding, debugging, and difficult tradeoffs among fidelity, calibration, latency, cost, and reliability.

Lead and develop a small team of Product Engineers while remaining hands-on in architecture, coding, debugging, and technical direction. Partner with Product and Design to define roadmaps, build reusable customer-facing capabilities, and establish quality standards for AI-native products. Own production reliability, security, permissions, latency, cost, observability, and incident follow-up. Recruit and mentor engineers, improve execution across workstreams, and create durable interfaces with platform, simulation, research, and deployment teams.

Own research on forecasting aggregate human behavior and future outcomes. Build datasets and predictive methods, including statistical models, language models, retrieval, and agent simulation. Design temporal holdouts and prospective evaluations; assess calibration, robustness, subgroup performance, uncertainty, and decision costs. Diagnose failures, compare complex approaches with strong baselines, document reproducible findings, communicate negative results, and hand validated methods to engineering for production deployment.

Own ambiguous customer problems end to end, from user discovery and system design through implementation, evaluation, rollout, measurement, and production support. Build full-stack, AI-native product experiences involving interfaces, APIs, data models, orchestration, permissions, integrations, and reporting. Establish evaluation criteria, instrumentation, reliability practices, and reusable product primitives while collaborating with product, design, platform, simulation, research, and customer-facing teams.

Lead and grow the Platform engineering team building APIs, workflows, and interfaces that make simulations usable. Set technical direction, make architecture decisions, write code, turn research into reliable product features, hire and mentor engineers, and deliver high-quality production systems in an in-person NYC environment.

Design and build the platform that powers AI-driven simulation products. Create abstractions and framework-level code, partner with research and product to integrate simulation capabilities, and own platform architecture through implementation and iteration to make complex capabilities accessible to diverse users.

Lead product design across Aaru's AI-native platform: identify user patterns, ship prototypes and features, evolve the design system, experiment with agentic workflows, and hire/build the design team.

Own the full enterprise sales cycle for Aaru's AI-driven behavioral simulation product: prospecting, discovery, scoping, pitching, negotiation, and close. Develop targeted outbound strategies, manage multi-stakeholder executive deals, expand market segments, refine go-to-market playbooks, and maintain disciplined pipeline hygiene, forecasting, and CRM-driven account plans.

Source and secure high-value third-party datasets by mapping the data landscape, outreaching to vendors, coordinating sample reviews, evaluating data quality and value, negotiating licensing and commercial terms, and maintaining vendor records while partnering with research, engineering, and leadership to prioritize acquisitions.

Build and maintain scalable pipelines to ingest, clean, and integrate large multimodal datasets. Own ingestion across APIs, files, cloud storage, and warehouses. Design linkage, entity resolution, deduplication, and schema harmonization. Implement data quality checks, validation, and documentation. Collaborate with engineering, research, and deployment teams to prepare integrated data for simulations and evaluate new data sources.