Top AI & Machine Learning Jobs

Build monday.com’s Agentic SDLC using AI and autonomous agents to automate the software delivery lifecycle from pull request through production. Develop full-stack applications, design scalable architectures, improve developer experience, and collaborate across R&D. The role requires cloud-based engineering, modern backend and frontend development, release-cycle ownership, and potentially DevOps practices using AWS, Kubernetes, and CI/CD.

Build and own AI-native, full-stack products from design through deployment and monitoring. Develop user experiences with React, Next.js, Node.js, and TypeScript; integrate LLMs; make architectural decisions; optimize performance and scalability; and improve reliability across cloud-based systems. Collaborate with product and design teams, validate AI behavior with evaluations, and establish engineering best practices for AI-powered products.

Design and ship AI-powered communication and notification features. Architect high-throughput, event-driven systems and background workers, improve performance and reliability, integrate AI models, and work across backend and frontend technologies. Collaborate with product and design teams to deliver customer-facing experiences while shaping API design, observability, and scalable architecture.

Build and ship production AI agents for monday.com’s Sidekick assistant, including tool use, reasoning, memory, context management, and agentic workflows. Own offline and online evaluation, observability, latency, cost, and quality improvements. Collaborate with product and design to develop AI features from prototype through production while applying current agentic techniques to ambiguous problems.

Leads data science for monday.com’s agentic product while directing a cross-R&D guild of approximately 10 data scientists. Responsibilities include building production agent evaluation systems, analyzing traces, improving model and tool-use quality, setting data science standards, mentoring and managing talent, hiring, and advising leaders on AI strategy and product decisions.

Own and evolve monday.com’s AI foundations platform, including generative AI products, agent frameworks, MCP tooling, identity and governance, secure data access, and production systems. Design scalable APIs, SDKs, and cloud-native infrastructure; implement authentication, authorization, observability, and agent security; take ambiguous initiatives from concept through production; and mentor engineers while setting technical direction.

Design and own evaluation methodologies, metrics, datasets, test suites, and pipelines for production AI agents. Build end-to-end evaluation tools, analyze agent execution traces and failure modes, establish quality standards, and embed continuous evaluation into engineering workflows. Partner with engineering and product teams to drive adoption, improve agent reliability, and guide production decisions across the organization.

Design and ship AI-first enablement solutions and content that teach product and business use. Rapidly prototype tools (agents, LLM workflows, no-code solutions), iterate from user feedback, deliver hands-on training, and collaborate across Product, Engineering, and client-facing teams to drive adoption and measurable impact.

Build Marko, a production-grade agentic marketing platform that autonomously manages advertising campaigns, creative generation, budget allocation, and performance optimization. Own specialized sub-agents, orchestration, tool integrations, approval gates, audit trails, evaluation systems, and feedback loops. Integrate major advertising platforms and collaborate with marketing leadership on campaign economics and attribution. This founding engineer role requires shipping reliable AI systems that operate at scale with real budgets.

Lead AI transformation engagements for 1–2 strategic enterprise customers. Partner with executives to define outcomes, architect and build production AI solutions, configure monday AI agents and vibe apps, integrate customer systems through MCP, and develop custom scripts. Own deployments from discovery through rollout and adoption, measure business impact, conduct workflow evaluations, and convert deployment insights into reusable assets, product requirements, and roadmap improvements. Collaborate with Sales, Customer Success, and Product as the technical authority.