Elm AI

HQ
New York
Total Offices: 3
12 Total Employees
Year Founded: 2023

Jobs at Elm AI

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Recently posted jobs

4 Days AgoSaved
In-Office or Remote
30 Locations
Artificial Intelligence • Logistics • Software
Build and deploy AI-powered software for customer workflows, including integrations, backend services, agent workflows, and user interfaces. Work directly with customers to understand requirements, prototype solutions, productionize them with monitoring and human review, diagnose rollout issues, and convert deployment insights into reusable product capabilities. The role requires strong cross-stack engineering, customer communication, product judgment, and hands-on experience with LLMs or AI agents.
Artificial Intelligence • Logistics • Software
Owns customer relationships from onboarding through adoption, expansion, and renewal. Maps workflows and data, identifies high-value AI opportunities, translates needs into implementation requirements, partners with product and engineering on deployments, leads rollout and adoption, tracks customer value, and develops repeatable customer success and deployment playbooks.
23 Days AgoSaved
Hybrid
New York, NY, USA
Artificial Intelligence • Logistics • Software
Generalist supporting founders in building Elm AI’s go-to-market function. Responsibilities span customer discovery, positioning, messaging, content, outbound outreach, partnerships, events, sales conversations, pilots, commercial discussions, and product feedback. The role will track customer and revenue outcomes, test new growth approaches, and help shape product direction. Supply-chain, procurement, or sourcing experience is preferred but not required. The position is full-time and hybrid or remote, ideally based in New York, with frequent customer and industry-event travel.
23 Days AgoSaved
Remote
International, Batken, KGZ
Artificial Intelligence • Logistics • Software
Build Elm AI’s core product and AI agent workflows across frontend, backend, and product experience. Own features from architecture through implementation, make scalable technical decisions, improve developer velocity and product quality, and establish practical AI-assisted engineering practices. The role requires strong product judgment, technical depth, ownership in ambiguous situations, and the ability to ship durable software in an international remote environment.