Merchandise Planner
•Cscgeneration· 15h
🏷️ Data Science⏰ Full-time📈 Mid Level🇺🇸 USA
15h ago
Loadsmart·about 20 hours ago
We are looking for a hands-on, business-minded, and relentlessly curious builder. This role sits at the intersection of AI technology and business operations, embedded within our R&D organization but working daily with Marketing, Sales, Finance, and other departments. You will identify high-friction workflows across these teams, translate them into AI agent solutions, and ship them. You are not a passive consultant: you prototype, you iterate, and you own outcomes. You bring enough technical fluency to build production-ready agents using modern LLM tooling, and enough people skills to earn trust from non-technical stakeholders.
LOCATION: Anywhere in Brazil - RemotelyPartner with Marketing, Sales, Finance leaders, and other business teams to identify repetitive, high-volume workflows that are strong candidates for AI automation.
Design and build AI agents using no-code and low-code platforms (Claude, n8n, etc).
Run discovery sessions with business stakeholders: map current-state workflows, document pain points.
Own the full delivery lifecycle: prototype, test with end users, iterate, and hand off with documentation and training.
Maintain a prioritized backlog of automation opportunities across business units, informed by business impact and implementation effort.
Build and run an internal AI Agents enablement program: run hands-on workshops, publish reusable templates and playbooks, and coach business teams so they can build and maintain their own agents over time.
3+ years in a business operations, process improvement, or technical enablement role.
Demonstrated hands-on experience building automated workflows or AI agents using modern tooling (n8n, Make, LangChain, Claude, or equivalent).
Comfort working with LLMs through prompt engineering: you know how to get reliable, structured outputs from a model.
Ability to conduct business process discovery with non-technical stakeholders and translate findings into actionable specs.
Fluent English; clear written and verbal communication for both technical and non-technical audiences.
Strong bias for shipping: you prefer a working prototype over a perfect design document.
SQL or Python for data extraction and lightweight scripting.
Familiarity with enterprise tools commonly used by business teams: Salesforce, HubSpot, Slack, Google Workspace, Netsuite.
Background in supply chain, freight, or logistics operations
Background in software engineering