Top Tech Jobs & Startup Jobs in NYC, NY

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.