Manager, Engineering

Immigration / Work Authorization Notice: At this time, iSpot does not provide visa sponsorship or immigration support for this role. Applicants must already be authorized to work in the United States on a full-time, permanent basis without the need for current or future sponsorship.

iSpot competes for the best talent. Our compensation packages consist of salary and equity in one of Seattle’s hottest start-ups, as well as other standard benefits. Most importantly, we provide a really interesting working experience, and the chance to contribute to the success of something great.

What You’ll Be Part Of:

We are seeking a Engineering Manager to lead the development of our high-scale Ad Platform infrastructure. This role is responsible for the mission-critical systems that ingest, process, and organize massive streams of media data. You will own the end-to-end data lifecycle, from ingestion of raw broadcast/digital signals to the management of a robust Content Catalog. This role has explicit accountability for software quality, owns the frontend, and brings ads domain expertise, including ownership of the ad catalog. Your objective is to ensure that our platform provides a highly accurate, performant, and "source-of-truth" foundation for all downstream measurement and attribution products. The role requires balancing people leadership, technical execution, and quality outcomes across all platform systems

Responsibilities:

Platform Evolution & AI Integration

• System Modernization: Lead the strategy for upgrading and refactoring existing ingestion and cataloging systems to improve throughput, reduce latency, and lower technical debt.
• AI-Driven Cataloging: Embed machine learning and AI into the content cataloging workflow to automate creative identification, metadata extraction, and fingerprinting at scale.
• Big Data Domain Expertise: Ensure the accuracy and reliability of massive ad datasets, partnering cross-functionally to evolve platform capabilities in support of complex attribution modeling.

End-to-End Lifecycle & Quality Accountability

• Full Lifecycle Ownership: Own the pipeline from design and development through testing, release, and post-release stability.
• Quality Gating: Define and enforce software quality standards. You are the final authority on release readiness, tracking metrics such as defect density, test coverage, and production uptime.
• Rigorous Testing: Ensure unit, integration, and regression testing are natively embedded in the CI/CD pipeline. Lead root-cause analysis (RCA) for any production incidents to drive continuous improvement.

Technical Execution & Agile Leadership

• Effective Sprint Planning: Translate long-term platform strategy into actionable, well-scoped sprints. Balance the delivery of new features with the maintenance of "always-on" ingestion systems.
• Frontend & Internal Tooling: While the focus is backend-heavy, you will own the architecture and usability of internal-facing tools and dashboards, ensuring consistency and performance for internal power users.
• People Leadership: Coach and mentor a team of engineers, fostering a culture of high accountability, ownership, and "quality-first" engineering.

Operational Reliability

• System Health: Ensure the 24/7 availability and performance of the ad catalog and ingestion engines.
• Agile Maturity: Drive agile best practices to ensure the team remains nimble while maintaining the discipline required for big data environments.

Qualifications and Education Requirements:

• Engineering Leadership: Proven experience managing high-performing teams delivering production-grade, distributed software at scale.
• Big Data: Deep domain expertise in big data architectures, specifically managing high-throughput data ingestion, or media metadata systems.
• System Modernization: Proven track record of upgrading legacy systems and refactoring technical debt into scalable, modern platform architectures.
• AI Implementation: Experience embedding AI/ML models into production workflows to automate content cataloging, creative identification, or data tagging.
• Full-Stack Oversight: Architectural proficiency in both backend data systems and frontend technologies used to build performant internal management tools.
• Lifecycle Ownership: Demonstrated accountability for the end-to-end software lifecycle, from initial de