Top Tech Jobs & Startup Jobs in Seattle, WA

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.

Provides advanced technical support and final escalation management for complex enterprise client issues. Troubleshoots data-driven applications, databases, APIs, networking, Java, Linux, and SAP environments. Supports implementation readiness, maintains shared technical environments, develops knowledge-base content, and partners with product, engineering, and support teams. Provides mentorship, process guidance, and rotational on-call support while managing high-stakes customer escalations.

Provides advanced technical support and final escalation management for complex customer issues involving data-driven applications, databases, APIs, enterprise systems, networking, Linux, and web services. Supports implementation readiness, maintains shared technical environments, develops documentation, partners with product and engineering teams, and mentors support staff. The role also includes on-call responsibilities, customer liaison work, and troubleshooting across SAP, Oracle, relational database, and integration technologies.

Develops corporate and business strategy through market research, customer segmentation, market evaluation, pricing, business model development, financial modeling, and growth analysis. Structures complex problems, leads cross-functional strategy workstreams, creates executive and board-level presentations, and delivers actionable insights in collaboration with senior leaders and external stakeholders.

Supports troubleshooting and resolution of complex client technical issues across enterprise applications, databases, APIs, web services, and cloud environments. Provides customer-facing assistance during implementation and ongoing support, documents solutions, contributes to knowledge bases, collaborates with internal teams, and participates in training, projects, and on-call rotations.

Serve as final escalation for complex, visible client technical issues; provide advanced troubleshooting for data-driven applications, databases, APIs, Java, Linux, and networking. Liaise with customers and internal teams during implementations, mentor junior staff, maintain shared environments, create knowledge-base documentation, and participate in on-call rotation.

Lead Vertex’s global Oracle partnership strategy and execution, including executive relationship management, joint business planning, solution integrations, co-selling, partner enablement, commercial alignment, and go-to-market initiatives. Coordinate cross-functional product, sales, marketing, solutions, customer success, and legal teams. Monitor pipeline, revenue, adoption, and strategic performance while managing risks and corrective actions. Lead a matrixed partnership team and serve as the executive spokesperson for the Oracle relationship.

Leads the design, administration, and continuous improvement of Customer Success technology infrastructure, particularly Gainsight, CRM integrations, workflows, playbooks, CTAs, health scores, digital engagement, community platforms, reporting, and AI-enabled automation. Owns data quality, governance, platform health, operational readiness, and process documentation while partnering cross-functionally on segmentation, territory alignment, capacity planning, and scalable customer execution.

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.