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Lead enterprise SaaS implementations for manufacturing customers, managing timelines, budgets, scope, risks, resources, executive stakeholders, training, workshops, and change management. Translate business requirements into platform configurations, resolve issues, support adoption, and improve deployment workflows. The role requires Boston-based hybrid work, customer-site travel, and US citizenship or permanent residency due to export-control requirements.

Own a book of strategic B2B SaaS customers to drive product adoption, retention, renewals, and expansion. Act as trusted advisor to executives, manage escalations, forecast renewal/expansion outcomes, identify growth opportunities, and collaborate across Sales, Product, and Support to improve customer ROI and outcomes.

Lead a small ML engineering pod to turn research into production: design and operationalize training pipelines and low-latency inference services for computer vision, document intelligence, and predictive models. Drive R&D execution, benchmarking, prototyping, migrations from frontier models to fine-tuned/open-source solutions, and mentor early-career engineers while aligning research with product timelines.