Manager, Engineering

Madrona Venture Labs; Bellevue (WA); Hybrid; USD 169,000 - 213,000; Full time

Benefits offered by this job

Equity plan

Job summary

iSpot is seeking an Engineering Manager to lead the development of our high-scale Publisher Team. You will own the end-to-end data lifecycle for the ad content catalog, overseeing ingestion, processing, and quality.

This role balances people leadership with technical execution to ensure a highly accurate, performant, source-of-truth platform for downstream measurement products. Key responsibilities include platform modernization, AI-driven automation, and integrating large data sources, while

Qualifications

• Proven experience managing high-performing teams delivering production-grade, distributed software at scale.
• Deep domain expertise in big data architectures and high-throughput ingestion.
• Experience upgrading legacy systems and refactoring debt into scalable platforms.
• Experience embedding AI/ML into production workflows to automate cataloging.
• Architectural oversight of backend data systems and frontend internal tools.
• End-to-end lifecycle ownership from design through post-release stability and performance.
• Defining and enforcing rigorous quality gates with automated tests.
• Production stability focus with data-driven metrics like latency and defect rates.
• Mastery of agile sprint planning for rapid delivery and long-term stability.
• Maintain high shipping cadence while upholding reliability and data integrity.
• Strategic collaboration across Product, Data Science, and Operations.

Responsibilities

• Lead strategy for upgrading ingestion and cataloging systems to improve throughput and reduce latency.
• Embed ML into content workflows to automate creative identification and metadata extraction.
• Own onboarding and maintenance of large third-party data sources such as ACR and streaming signals.
• Own the pipeline from design to release and post-release stability.
• Define and enforce software quality standards; ensure release readiness with metrics.
• Ensure unit, integration, and regression testing in CI/CD; drive RCA for incidents.
• Translate platform strategy into actionable, well-scoped sprints.
• Own architecture and usability of internal tooling and dashboards.
• Coach and mentor engineers; foster ownership and quality-first culture.
• Champion AI-assisted development practices with rigorous review processes.

Skills

Engineering leadership

Big data

System modernization

AI implementation

Full-stack oversight

Lifecycle ownership

Quality governance

Agile execution

Delivery velocity

Strategic collaboration

Job description

Immigration / Work Authorization Notice: Applicants must be currently authorized to work in the United States. iSpot is not able to sponsor or take over sponsorship of an employment visa for this position at this time.

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 Publisher Team. 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.

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 Automation: 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.
• Partner Data Integration: Own the engineering work to onboard and maintain large third-party data sources (ACR, set-top-box, streaming, and panel signals), including the migration and cutover work that comes with changing providers.

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.
• AI-Enabled Engineering: Champion the adoption of AI-assisted development practices across the team, holding the same standards for quality and review that apply to all code we ship.

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 design through to post-release stability and performance.
• Quality Governance: Experience defining and enforcing rigorous quality gates, including automated unit, integration, and regression testing frameworks.
• Operational Excellence: Strong focus on production stability, using root-cause analysis and data-driven metrics (e.g., defect rates, latency) to drive improvement.
• Agile Execution: Mastery of effective sprint planning to balance rapid delivery of new platform features with long-term infrastructure stability.
• Delivery Velocity: Ability to maintain a high shipping cadence while upholding strict standards for system reliability and data integrity.
• Strategic Collaboration: Exceptional communication skills to align engineering efforts with Product, Data Science, and Operations objectives.

Preferred Skills:

• Ad Tech Platform experience
• Ad tech, media measurement, or audience measurement platform experience
• Familiarity with publisher-side or sell-side measurement - audience delivery, reach and frequency, cross-platform de-duplication
• Exposure to ACR, set-top-box, panel, or streaming census data sources
• Experience managing engineering work tied to enterprise partner SLAs and contractual delivery dates

Target cash compensation range: $168,529 - $212,710 USD Annually

We are committed to providing competitive, market-informed compensation. The cash compensation above includes base salary, variable commission for employees in eligible roles, and annual bonus targets for eligible roles. In addition to cash compensation, all full time iSpots are eligible to participate in iSpot's equity plan to receive stock options. Non-exempt roles will also be eligible for (pre-approved) overtime pay. Individual compensation packages are influenced by different factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons.

For more information on total rewards package, go HERE

Hybrid & Flexible Workplace Policy

iSpot supports a hybrid and flexible workplace. Depending on location and work responsibilities, employees may be designated as full-time or part-time office-based or a fully remote employee. A hybrid work schedule indicates that you work in the office some days and work from home other days. The best hybrid workplaces allow for flexibility while also encouraging consistency.

Those local or living in surrounding areas to one of our offices (Bellevue, WA or New York, NY) will work a hybrid schedule, coming into their local office 1-3 days a week. While those in a role, not office-based and located further away from our offices, will work a fully remote schedule.

#LI-Hybrid

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