Top Tech Jobs & Startup Jobs in Seattle, WA

Own product launch and release enablement programs while developing targeted enablement for Solutions Consultant and Overlay teams. Create scalable eLearning, demo videos, playbooks, technical content, and live training. Partner cross-functionally with Product, Product Marketing, GTM leadership, and role enablement teams. Use reporting systems and AI tools to identify gaps, measure adoption, and drive behavioral and business outcomes.

Leads enterprise data platform architecture, engineering standards, technical decisions, and development of scalable data products. Designs batch and streaming systems, governance, observability, security, and reliability practices. Partners cross-functionally, mentors engineers, drives modernization and migrations, and establishes reusable patterns for data modeling, orchestration, quality, and platform operations.

Leads the strategy, roadmap, and development of ZoomInfo’s agentic platform, including orchestration, planning, memory, tools, guardrails, observability, custom models, and decisioning capabilities. Partners with engineering and data science to deliver production-grade infrastructure, conducts orchestration R&D, launches new platform capabilities, and builds a senior product management organization.

Build and operate production infrastructure for entity-focused AI agents. Responsibilities include scheduled benchmarking and golden gates, scalable entity-agent pipelines, evidence adapters, replayable vendor stores, agent-platform deployment, review and batch tooling, rollback mechanisms, and comprehensive cost, quality, latency, and health instrumentation. The role partners with AI engineering, product, research, data, and platform teams to move prototypes into reliable, self-service production systems.

Architects and standardizes cloud infrastructure for data platforms on GCP, including Kubernetes, networking, Terraform, GitOps, CI/CD, observability, performance, cost, security, and disaster recovery. Evaluates emerging data technologies, runs prototypes, guides managed-service connectivity, supports governance and consolidation, and enables engineering teams through architecture reviews, workshops, reference implementations, and documented standards.

Own the person-data product portfolio, including accuracy, coverage, freshness, compliance, entity resolution, and privacy. Build the AI evaluation system for agent-generated records using golden sets, thresholds, human adjudication, precision, recall, and drift monitoring. Lead the transition from deterministic rules to agent-based processing, collaborate with engineering and data science, prototype in code, and drive cross-functional roadmap execution.

Own ZoomInfo’s growth product portfolio from acquisition through activation, monetization, expansion, and sales-assist routing. Define multi-quarter PLG strategy, run high-volume experimentation, analyze funnels and cohorts using SQL and Snowflake, design self-serve experiences and consumption-based pricing, and present growth economics to executives. Partner across engineering, design, marketing, sales, and customer success while hiring and coaching growth PMs and establishing experimentation standards.

Own ZoomInfo’s global data partnership and supply strategy, including build-buy-partner-acquire decisions, strategic data agreements, co-sell motions, acquisition theses, supplier portfolio economics, and data-quality evaluations. Lead executive partner relationships and cross-functional deal execution across sales, product, legal, privacy, security, procurement, and corporate development while ensuring compliance with global privacy regulations.

Lead product for GTM Studio features across audience building, AI enrichment, and AI orchestration. Partner with engineering, data, AI platform, design, and customers to build integrations, ensure data quality and freshness, and deliver go-to-market orchestration tools for revenue operators.

Own strategy and roadmap for identity resolution engines that match visitors to people and companies. Drive data source integrations, improve match accuracy, resolve data quality issues, build monitoring, collaborate with engineering and data science, and enable GTM teams while ensuring privacy compliance (GDPR/CCPA). Measure impact via match rates, coverage, latency, and downstream revenue.