ZoomInfo

AI Engineer

• Run the benchmark and golden-gate system on a schedule against staging, automatically gating agent versions and tracking variance and drift
• Complete the entity-agent pipeline, including enricher fan-out, location sets, hierarchy batch files, and production-scale classifier migration
• Measure throughput and unit cost per pipeline stage on named cohorts
• Build evidence adapters for registries, live web, mail-tenant signals, and external research vendors behind a replayable, swappable envelope
• Deploy company and contact agents onto ZoomInfo’s Agentic Platform, including ingest adapters, bulk intake, rollback paths, and lockstep implementation upgrades
• Build review queues, tagging tools, blast-radius viewers, and batch runners for self-service use by researchers and product managers
• Own the health and deployment of classifiers, agents hub, and judge platform inside internal tooling
• Instrument cost, latency, quality, and alerts across systems
• Collaborate with the Principal AI Engineer, product managers, research team, agentic platform team, and company and person engineering teams
• Report to the Senior Manager of Product for Core Data, with the Principal AI Engineer as technical lead

Principal Applied AI Engineer – Entity Agents

Infrastructure Engineer

• Partner with ZoomInfo's data engineering organization as the infrastructure architecture counterpart
• Establish and maintain infrastructure-as-code, CI/CD, monitoring, alerting, performance, and cost patterns for data teams
• Design reference patterns for streaming, messaging, databases, analytics stores, search, orchestration, processing, and open table formats
• Define CI/CD and GitOps patterns for data jobs and pipelines
• Establish performance, cost, observability, backup, restore, and disaster recovery patterns, including RTO/RPO targets
• Run proofs of concept for emerging data technologies and vendor offerings
• Define secure connectivity patterns between managed data services and ZoomInfo's GCP environment
• Support data consolidation, governance, classification, residency, and access-policy efforts
• Build reference implementations, write ADRs, and partner with owning teams on rollout
• Participate in weekly architecture reviews, expand standards and ADR libraries, and provide infrastructure consulting
• Host design reviews and workshops and enable data teams through complex infrastructure decisions

Principal Infrastructure Architect – Data Platform

Machine Learning Engineer

• Extend ZoomInfo's data graph into the long tail of companies with little public footprint by extracting leadership, locations, and products from company websites and detecting stale records
• Predict headcount and revenue for under-documented companies using gradient-boosted trees, regression with missing inputs, and calibrated uncertainty
• Determine whether records describe the same company or person and measure wrongly merged and wrongly split outcomes
• Infer buying intent from multilingual, noisy web content to support propensity scoring, lookalike retrieval, and contact recommendations
• Build agents that research companies and cite sources, and design evaluations distinguishing correct results from runs that merely finished
• Distill large models into smaller cost-effective models, owning quantization and serving
• Take ambiguous, high-stakes problems from undefined to shipped
• Raise the team's engineering bar through review, design, and mentorship

Artificial Intelligence

• Lead the team building the intelligence underlying ZoomInfo AI agents, including the B2B data graph, training data, model serving, machine learning, data science, LLMs, and agentic systems
• Extend ZoomInfo's B2B data graph into the long tail to improve comprehensiveness and accuracy
• Lead work on agent memory, distinguishing user-supplied information from system-of-record data
• Select classical machine learning, language models, or code for each problem based on measured evidence
• Define evaluation standards for models and agents, including evaluation datasets, regression gates, and experiment designs
• Own inference cost, latency, and capacity, including build-versus-buy and distillation decisions
• Hire and develop machine learning engineers, data scientists, and research engineers
• Represent the team's work across product, platform, security, and legal, and present results and limitations to executives
• Set standards for using agentic coding tools through precise specifications and rigorous code review

Director, Applied AI

Product Manager

• Own vertical datasets end to end, including sourcing, development, entity resolution, delivery, pricing, packaging, and revenue generation
• Define dataset audiences, coverage, accuracy, quality standards, and completion criteria
• Partner with data engineering and platform engineering to deliver datasets from the warehouse to the GTM Data Store, APIs, MCP, and applications
• Write requirements, define use-case queries, own testing, and drive handoffs
• Own pricing and packaging, including price-book placement, licensing models, supplemental terms, and bundling
• Enable product-led and sales-led commercialization through in-product discoverability, sales materials, data reference guides, use cases, positioning, and sales support
• Work directly with strategic customers and sales teams to understand needs and shape datasets and offers
• Build vertical solutions and workflows by packaging datasets together
• Coordinate data quality, engineering delivery, pricing, legal terms, and marketing across teams
• Prioritize dataset investment based on revenue potential, customer demand, and core-data value
• Feed customer and delivery learnings back into future product development

Principal Product Manager – Vertical Data

Sales

• Lead and develop a team of 8 enterprise account managers, driving revenue targets and building a culture of accountability, performance, and continuous growth
• Coach and develop the team daily by tracking KPIs, running deal reviews, and improving territory strategy, stakeholder engagement, and value-based selling
• Develop and execute account penetration strategies, including account mapping, stakeholder engagement planning, competitive displacement, and expansion plays
• Define team objectives and manage forecasts, translating quarterly targets into daily and weekly priorities
• Build cross-functional relationships across marketing, demand generation, product, customer success, legal, deal desk, and engineering
• Manage internal sales processes and coordinate complex enterprise deals
• Articulate ZoomInfo’s value proposition by connecting its platform to customer GTM vision, business outcomes, and ROI
• Participate in attracting and hiring top talent
• Own budget planning, performance management, and strategic planning as directed by senior leadership

Principal Applied AI Engineer – Entity Agents

Principal Infrastructure Architect – Data Platform

Machine Learning Engineer

Director, Applied AI

Principal Product Manager – Vertical Data

Regional Sales Director, Enterprise