Top Artificial Intelligence Jobs

Own the commercial and strategic health of a SaaS customer portfolio, including renewals, expansion, QBRs, account planning, stakeholder relationships, and proactive communication. Partner with customer success counterparts and agency partners to align platform experience with account strategy. Maintain accurate client documentation and identify upsell opportunities by understanding customer goals, usage patterns, and business value.

Own Butter’s product-led growth engine, improving activation, time to value, retention, monetization, onboarding, and in-product sharing loops. Define aha moments, identify workflow friction, run weekly experiments, analyze cohorts, model LTV, establish CAC guardrails, and build a data-driven growth roadmap. Partner closely with Design and Engineering while establishing growth processes and eventually building the product growth team.

Lead architecture and end-to-end delivery for Sylvan’s autonomous revenue platform. Build initial versions of complex systems, guide ML and product strategy, establish engineering standards for agent-driven development, and lead a pod of three to four engineers. Responsibilities include sprint planning, technical design, infrastructure decisions, hiring, performance management, and shipping production work with significant autonomy.

Open the New York market for an AI-native legal services business targeting banks, funds, insurers, and other regulated institutions. Build pipeline from zero, engage senior legal and compliance buyers, run complex enterprise sales cycles, coordinate proposals with lawyers, navigate procurement and security reviews, develop positioning and repeatable sales processes, and establish CRM, reporting, and automation. The role will own the commercial motion and eventually hire and scale the team.

Design and implement high-performance algorithms for robotic guidance, inspection, 3D perception, and navigation in dynamic industrial environments. Build production-ready C++ software, optimize real-time embedded systems, and contribute throughout development from prototyping through deployment. Collaborate across teams to deliver commercial robotics solutions for manufacturing and maintenance applications.

Lead video editor responsible for producing long- and short-form content, motion graphics, promotional assets, and select design projects. The role involves hands-on editing, visual storytelling, AI-assisted content creation, developing templates and visual standards, and managing freelance creative contractors. The editor will collaborate with founders and internal teams to shape the company’s visual identity across video, social, web, and promotional channels.

Leads pre-sales consulting and solution advisory for Atlassian Cloud and related digital transformation solutions. Responsibilities include customer discovery, requirements gathering, solution architecture, demonstrations, proof-of-value initiatives, licensing recommendations, proposal development, technical advisory, and selected delivery engagements. Supports cloud migrations, application modernization, system integration, managed services, and business development while coordinating with sales, architecture, delivery, and partner teams.

Design and own foundational systems for enterprise AI agents, including distributed agent pipelines, automation editors, graph traversal and indexing systems, and frameworks for autonomous workflow execution. The role focuses on scalable, deterministic, auditable, multi-tenant-safe architecture across complex enterprise data environments. Founding Engineers will work as high-slope generalists, owning architecture, product development, production-quality code, and customer impact in an ambiguous, fast-moving environment.

Enterprise Account Executive responsible for managing enterprise customer accounts and driving sales growth. The demo posting provides no further details about duties, qualifications, compensation, travel, or work authorization.

Design, train, and deploy ML models for Qur'ān recitation, tajwīd detection, and ASR. Build data pipelines for cleaning, segmentation, labeling, and evaluation. Integrate real-time predictions via APIs or lightweight on-device inference, optimize models for speed and mobile performance, and collaborate with backend developers to ship AI features in the app.