Sr. Engineering Manager, Programmatic Ad Tech, tvScientific

The Ad Server team at tvScientific is seeking a technical leader to oversee tvScientific's emerging ad server stack and help drive the ad server independence initiative.

Responsibilities:

• Lead and make key architectural decisions across the tvScientific ad server tech stack and its major integration points.
• Take technical ownership of the ad server independence roadmap, including developing a clear understanding of the current state of initiatives, ownership across subcomponents, and resourcing needs.
• Oversee and organize the subteams supporting the initiative, including bidder, index building, and VAST serving.
• Serve as the technical DRI for bidder integration work with Pinterest, partnering closely on milestone sequencing, delivery planning, and execution.
• Identify and drive opportunities for shared components and common infrastructure with Pinterest where it makes strategic and technical sense.
• Participate in key strategic technical roadmap and architecture decisions for the Ad Server team.
• Help scale the team over time, including supporting the growth of a multidisciplinary engineering organization.

Requirements:

• Bachelor's degree in Computer Science, Engineering, a related field, or equivalent practical experience.
• 9+ years of software engineering experience, including 5+ years of ad industry experience with 3+ years deep in programmatic ad tech.
• 5+ years of engineering management experience.
• A history of designing scalable, resilient, and observable production systems.
• Demonstrated ability to build and operate high volume, data-intensive services.
• Experience working with ML in low-latency environments.
• Strong data literacy and the ability to use data to inform technical and strategic decisions.
• Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs.
• Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review).
• High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.