Jobs at Vertex, Inc.

Lead end-to-end strategic relationships for high-value accounts using AI-driven insights to drive value realization, retention, and expansion. Manage risk with predictive signals, run executive engagements, coordinate cross-functional teams, drive adoption and renewals, and influence product strategy through customer feedback.

Generate and qualify outbound pipeline within an assigned territory using multi-channel outreach and AI-powered sales tools. Collaborate with Account Executives to develop territory strategies, engage senior stakeholders, maintain CRM data, meet quotas, and support sales operations. Travel up to 25% and contribute to territory planning and cross-sell/upsell efforts.

Lead strategy and execution for AI-powered Customer Success Services, overseeing Gainsight and related platforms, customer community strategy, customer intelligence, automation, digital engagement, platform governance, and a team to scale adoption, retention, and operational efficiency across the customer lifecycle.

Design and evolve cybersecurity operations architecture, lead detection engineering and log ingestion strategies across cloud and SaaS, implement AI-augmented detection and response pipelines, conduct security architecture reviews, improve incident response and threat hunting, mentor SecOps teams, and advise leadership on operational risk and tooling decisions.

Lead design and delivery of AI-first product capabilities for Vertex customers. Translate ambiguous tax-related problems into hypotheses, prototypes, and product requirements. Partner with SMEs, engineering, UX, GTM, and customer success to ship trusted, compliant, production AI, define evaluation and monitoring, manage roadmaps, and scale solutions with measurable customer and business outcomes.

Design, prototype, and deploy production-ready AI products using ML and generative AI. Lead cross-functional teams, collaborate with stakeholders to solve workflow problems, build scalable prototypes and proofs-of-concept, and apply latest ML/GenAI research techniques.

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.

The Software Architect will lead AI quality evaluation, design evaluation frameworks, create risk controls, and ensure compliance, partnering with various teams on AI systems.

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.