Jobs at Vertex, Inc.

Own the full enterprise sales cycle across the Midwest, from prospecting and territory planning through negotiation and close. Build executive relationships, manage complex multi-stakeholder deals, align tax technology and enterprise software solutions to customer outcomes, and exceed revenue quotas. Use AI-enabled tools and data to improve pipeline development, forecasting, and sales productivity while collaborating with marketing, consulting, sales development, and customer success teams.

Delivers GTM commercial analysis, dashboards, reporting, forecasting, workflow automation, and AI-assisted solutions. Partners with commercial, Finance, Data & Analytics, IT, and regional teams to improve decision-making, standardize metrics, validate outputs, resolve data issues, and reduce manual work. Owns assigned initiatives, documents business logic, supports testing and adoption, and develops reusable capabilities across regions.

Prepare and process 750+ monthly sales and use tax returns for complex clients. Onboard clients, reconcile tax data, resolve compliance issues, manage tax notices, and support electronic filings. Build process efficiencies using Excel, Microsoft 365, VITR, and automation tools. Lead improvement teams, document procedures, mentor junior staff, and communicate with clients while managing peak-period workloads.

Prepare more than 700 monthly sales and use tax returns for complex clients, resolve reporting issues, onboard clients and data files, investigate discrepancies, and support electronic filings and tax authority notices. Maintain compliance reports using Vertex Indirect Tax Returns, Excel, RPA, and Alteryx. Build client relationships, mentor junior staff, and contribute to process improvements while meeting peak-period deadlines.

Own complex enterprise software support cases from assignment through resolution, including executive escalations and critical incidents. Troubleshoot databases, APIs, cloud platforms, ERP and eCommerce integrations, authentication, networking, and infrastructure. Lead root cause investigations, mitigation, recovery, and cross-functional resolution efforts. Document knowledge and troubleshooting procedures, collaborate on defects and fixes, use AI-enabled support tools, mentor team members, and improve support processes while participating in on-call rotations.

Lead enterprise model-training strategy for Commercial AI products: fine-tune LLMs (QLoRA/LoRA/PEFT), train traditional ML models, design large-scale data pipelines, enforce data governance and PII handling, build reproducible experiment/training pipelines, optimize GPU/distributed training costs, and mentor teams to operationalize models into production.

Lead design and implementation of the enterprise AI orchestration and retrieval platform: build MCP servers, define tool-surface and multi-agent patterns, design RAG systems and chunking, implement routing/context/window management and observability, set evaluation and safety standards, onboard product teams, and mentor engineers to raise orchestration and retrieval maturity.