Top AI & Machine Learning Jobs

Own go-to-market for monday CRM AI: develop and package AI use cases, create high-cadence content, activate sales field with plays and demos, influence product roadmap, build GTM partnerships, and drive AI adoption and revenue.

Lead a 0-to-1 product area building AI trust for autonomous agents: define strategy, design trust and governance surfaces, run research and experiments, work closely with enterprise customers, and drive cross-functional execution to enable safe, transparent, scalable agent adoption.

Lead vision and roadmap for an AI-powered no-code app builder. Drive ideation, prototyping, and validation of generative AI features. Lead cross-functional teams to deliver and scale product impact, define success metrics, and partner with GTM and customer success to drive adoption and integrations across the monday platform.

Lead AI transformation projects for enterprise customers using monday.com and generative/agentic AI to design AI-powered workflows, build configurations and integrations, manage projects, present to executives, mentor junior consultants, and influence product roadmap and practice development.

Lead enterprise AI transformation and implementation projects on the monday.com platform, designing AI agents, automated workflows, and dashboards. Manage executive relationships, deliver project plans, run consultations and presentations, mentor junior consultants, drive adoption, and influence product roadmap while partnering on migrations, integrations, and practice improvements.

Lead the developer-focused AI product vision and roadmap, build agentic developer tools and infrastructure, drive adoption through user research and metrics, coordinate cross-organizational initiatives, and ship AI-powered developer workflows and integrations while measuring quality and impact.

Design and build AI-native products from 0→1, owning full-stack features through design, implementation, deployment, and monitoring. Lead architecture, integrate LLMs and AI tooling, optimize performance and reliability, and define best practices while collaborating with product and design.

Design and build AI-native systems and agent orchestration from 0→1. Own model quality lifecycle, evaluation frameworks, production monitoring, and continuous improvement. Rapidly experiment with models, prompts, and architectures, and collaborate with product and engineering to deploy reliable, scalable AI features.

Lead and mentor a full-stack engineering team to design, build, and operate production infrastructure for generative AI capabilities. Collaborate with data scientists and product teams to deploy LLMs/AI agents, evolve platform architecture, enhance the data layer, and support scale for millions of users.

Lead end-to-end AI initiatives for the Customer organization: translate company AI strategy into executable plans, support GTM and launches, design operational processes, define KPIs, analyze performance, and drive cross-functional alignment and communications while building frameworks and executing in ambiguous, fast-paced environments.