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The Technical Account Manager will serve as a technical advisor to paper and pulp customers, optimizing product implementation and fostering relationships to improve operations and drive retention.

Responsible for analyzing KPIs, leading financial planning processes, providing insights to sales and marketing, and preparing financial reports for senior leadership.

Entry-level Project Engineer supporting the Equipment & Engineering Team. Assist with pilot projects, testing, and validation; develop and standardize equipment designs; create and maintain drawings, schematics, manuals, specifications, and SOPs; support mechanical system layout and system integration (controls/automation); participate in design reviews, root cause analysis, and continuous improvement. Up to 10-20% travel.

The Sr. Payroll Specialist manages payroll processing for US and Canada, ensures compliance with tax regulations, audits payroll accuracy, and provides customer service to employees.

The Technical Account Manager acts as a technical advisor for key customers in paper and pulp, ensuring effective product implementation and optimization.

Remote Gulf Coast territory sales role responsible for generating new business, managing key accounts, growing sales of chemical treatment and manufactured products, collaborating with R&D, tracking sales activity, and traveling up to 25%. Requires prospecting, negotiation, technical on-site testing, and strong customer-focused relationship management.

Remote Midwest-based sales role responsible for growing and managing chemical treatment accounts. Generate leads, prospect, cold-call, close new business, manage key accounts, collaborate with R&D, perform on-site testing, track sales activity, and travel up to 25%. Must live in specified Midwest states and have chemical/industrial sales experience, including soda ash.

Own the end-to-end analytics product delivering trended insights and AI-driven recommendations. Define vision, roadmap, and backlog; lead pilots, validate in-field value, scale deployments, support commercialization and adoption, own business case and metrics, mitigate technical/operational/commercial risks, and drive evolution toward machine-learning insights.