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iSpot.tv

TV ad attribution with real-time analytics

Vice President Engineering

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeBellevue, WA, USA$226.3k - $296.4k /yrHybrid

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, or a related technical field is required; an advanced degree is preferred.
  • 15+ years of technology experience, including 5+ years leading engineering organizations through managers.
  • Proven track record of shipping and operating large-scale, data-intensive SaaS products in production.
  • Depth in distributed systems, cloud infrastructure, and modern data platforms and pipelines.
  • Experience leading cross-functional delivery spanning engineering, product management, and data science.
  • Strong technical depth and willingness to remain hands-on when necessary.
  • Demonstrated success building engineering culture, raising the talent bar, and retaining strong teams.
  • Demonstrated success operating in fast-paced, high-growth environments and driving organizational change.
  • Strong understanding of enterprise security, privacy, and data governance.

Responsibilities

  • Own end-to-end engineering execution for the Creative, Audience, and Outcomes product lines, including delivery, quality, reliability, and cost.
  • Build, lead, and develop an engineering organization, including hiring, leveling, performance management, and succession planning for managers and senior engineers.
  • Partner with Product Management to translate strategy into achievable roadmaps, realistic commitments, and clear delivery milestones.
  • Set technical direction and architectural standards for scalable, secure, and maintainable systems across data pipelines, services, and customer-facing applications.
  • Drive operational excellence across uptime, incident response, on-call health, observability, data quality, and continuous reduction of technical debt.
  • Establish and improve the engineering operating model, including planning cadence, software development lifecycle practices, code review standards, testing strategy, and release management.
  • Champion AI-assisted engineering practices to raise developer throughput and quality across the organization.
  • Partner with Data Science to productionize methodology, models, and measurement logic at scale.
  • Manage engineering budget, vendor relationships, cloud spend, and capacity planning against business priorities.
  • Ensure security, privacy, data governance, and compliance requirements are embedded in how the organization builds and operates.
  • Define and report metrics including delivery predictability, defect and incident rates, platform performance, unit economics, and team engagement.
  • Represent engineering with executives, customers, and partners, communicating trade-offs and progress.
  • Lead AI product strategy and execution across the Creative, Audience, and Outcomes product portfolio; identify and scale AI solutions that create business value and product differentiation.
  • Identify opportunities to apply generative AI, agentic systems, machine learning, and advanced analytics to customer experiences and business outcomes.
  • Lead incubation, prototyping, and commercialization of AI-powered products and features for creative intelligence, audience measurement, and outcome attribution.
  • Partner with Product and Engineering leaders to embed AI capabilities into products and roadmaps.
  • Establish technical direction and architectural patterns for scalable, secure, and responsible AI systems.
  • Build and lead an AI organization of engineers, scientists, and product specialists focused on customer-facing innovation.
  • Drive experimentation frameworks to validate AI concepts while maintaining execution discipline.
  • Collaborate with customers, partners, and commercial teams to understand market needs and develop AI capabilities.
  • Evaluate emerging AI technologies, vendors, and platforms to accelerate time-to-market and business impact.
  • Embed responsible AI practices, governance, security, privacy, and compliance in customer-facing solutions.
  • Define AI initiative success metrics, including customer adoption, revenue impact, operational efficiency, and product differentiation.
  • Represent iSpot externally on AI innovation in advertising, media measurement, audience intelligence, and marketing technology.

Desired Qualifications

  • Experience within advertising technology, media measurement, marketing technology, or consumer insights platforms.
  • Experience with large-scale data processing and analytics platforms, including streaming ingestion, warehousing, and identity resolution.
  • Experience integrating AI and agentic capabilities into products and the software development lifecycle.
  • Familiarity with modern DevOps, Site Reliability Engineering, and MLOps practices in cloud-native environments.
  • Experience leading platform migrations, replatforming efforts, or post-acquisition technical integration.
  • A master's degree or advanced technical degree is preferred.
  • Experience building and deploying agentic AI systems and autonomous workflows in production environments.
  • Familiarity with modern MLOps practices and cloud-native AI platforms.
  • Track record of creating new products or revenue streams through AI-enabled capabilities.
  • Experience working directly with enterprise customers to shape product strategy and innovation priorities.

About the Company

iSpot.tv

TV ad attribution with real-time analytics

iSpot.tv measures TV advertising effectiveness by linking ads to real-world actions like online activity, store visits, and sales. It collects a catalog of TV ads, airings data, and data from 12 million opt-in Smart TVs to deliver real-time impression and attention metrics through a subscription platform that integrates with a client’s marketing tools. This differs from competitors by providing real-time, outcome-based analytics that connect TV exposure to actual business results, not just impressions, with seamless integrations for planning and optimization. The goal is to help disruptive brands maximize TV ad ROI by tracking outcomes, optimizing campaigns, and aligning TV plans with business objectives.

Company size
201-500
Company stage
Growth Equity (Venture Capital)
Total funding
$382.8M
Headquarters
Bellevue, WA
Founded
2012

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