Jobs at Portcast

Own full enterprise sales cycle across the Americas for Freight Forwarders, LSPs, and BCOs: build pipeline, close complex deals, manage forecasting and CRM hygiene, and collaborate cross-functionally to ensure successful customer onboarding and product-market fit.

Own data quality and root-cause analysis for prediction issues: detect anomalies, trace sources, fix processes, automate QA/reporting with Python and SQL, maintain dashboards, and partner with Data Science, Engineering, Product, and Commercial teams to improve prediction performance and customer-facing analytics.

Support data integrations and quality by checking ingested/system-generated data for anomalies, building and running QA checks and automations with Python and SQL, assisting on customer data queries and dashboards, and documenting findings to improve prediction reliability.

Lead Portcast's end-to-end marketing function, focusing on product marketing, event strategy, cross-functional alignment, team leadership, and data-driven demand generation to drive pipeline and revenue for an enterprise B2B SaaS logistics platform.

Own full enterprise sales cycle across the Americas for freight forwarders, LSPs, and BCOs. Build pipeline, manage complex opportunities, close new customers, develop territory plans, and collaborate cross-functionally to influence product and GTM while maintaining CRM hygiene and forecasting.

Own full enterprise sales cycle across the Americas for freight forwarders, LSPs, and BCOs. Build pipeline through outbound prospecting and partnerships, manage complex deals, negotiate contracts, and ensure CRM hygiene. Develop territory plans, collaborate cross-functionally with Product/Marketing/Customer Success, and drive forecasting and pipeline reporting.

Design, build, and maintain backend APIs and services for a real-time supply chain visibility platform. Own system architecture, real-time event ingestion, data normalization, ML integration, monitoring, and production debugging while collaborating with Product and Data Science to deliver scalable, high-availability features.

Lead and align Engineering, ML, and Analytics to deliver scalable, reliable production AI and data systems. Own technical direction, architecture, MLOps, and platform reliability while partnering with Product, Sales, and Customers to ensure engineering work maps to measurable business outcomes.