Senior Engineering Manager, Backend (Content Foundations)

Content Foundations is a newly formed team at the center of Scribd, Inc.'s biggest strategic investment. Behind our UGC brands (Scribd and Slideshare) sits one of the largest corpora of human-created knowledge anywhere: hundreds of millions of documents and presentations. Every piece of that knowledge passes through one system. It's uploaded, understood, transformed, and served to millions of customers, and agents that cite it, ground it, and learn from it.

Content Foundations owns that system, and its work lands in two places at once. It powers the product roadmap: faster uploads, richer document experiences, and the growth of the corpus. And it operates as a platform for the teams that build on it: trust & safety, content understanding, supply, and AI platform teams all consume its interfaces. What this team ships translates directly into product outcomes for users and velocity for every team downstream. Content sits at the very top of Scribd, Inc.'s strategy: it's the engine of our consumer brands and the foundation of our growth, and the ingestion platform is where all of it begins.

We're hiring the engineering manager for Content Foundations to build and lead the team that owns how content enters Scribd. This is a leadership role at the intersection of large-scale data infrastructure and applied AI, and it carries three responsibilities in equal measure.

You'll be the technical leader for the platform: setting the vision for real-time, AI-native ingestion, making the architectural calls that evolve a live, high-scale system, and holding the quality and reliability bar for a system the whole company depends on.

You'll be the people leader for the team: hiring, growing, and inspiring a group of backend and AI data engineers, and shaping its culture, standards, and identity from its first days.

And you'll be the partner the content organization plans around: running the team's roadmap as a product, making commitments other teams can build against, and representing the platform in decisions with product and engineering leaders across the company.

The industry is redefining what document ingestion means. Documents can now be parsed, classified, safety-checked, and enriched in real time at the moment of upload, before they ever reach a reader, with vision-language models and intelligent chunking replacing what OCR and batch pipelines used to approximate. You'll bring those capabilities into one of the world's largest document platforms, with the corpus scale to make it matter.

Own the vision and strategy for how content enters Scribd, and lead the evolution of one of the world's largest document platforms into a real-time, AI-native ingestion system.

Build state-of-the-art AI into the heart of the platform, partnering with ML and AI teams so that every document is understood, trusted, and enriched by intelligent systems from the moment it arrives, and is ready for both human readers and AI agents.

Turn platform capability into product impact, partnering with product to deliver the supply-side roadmap, make our content discoverable by readers, groundable by AI assistants and create visible wins for the contributors who grow the corpus.

Lead, grow, and inspire a founding team of backend and AI data engineers, shaping its culture, hiring, technical standards, and career growth from day one.

Run the team as a product, defining the roadmap, priorities, and commitments that teams across the content organization plan against, and building the operational excellence of a system the whole company depends on.

Champion security as first-class design principles, building a platform that safely processes untrusted content at massive scale and safeguards the corpus.

Influence across the organization, partnering with senior product and engineering leaders across trust & safety, content understanding, supply, and AI platform teams to sequence one shared content mission.

8+ years in software engineering, including 3+ years leading backend, data-infrastructure, or platform engineering teams.

Depth in high-throughput distributed systems and data pipelines: streaming and event-driven architectures, ingestion and transformation at scale, and the judgment to evolve a live, high-volume system toward real time while it keeps running.

Enthusiasm for applied AI in production systems, with experience (or strong intent) integrating ML models, LLM-based document processing.

A platform-product mindset: you've built systems other teams and product surfaces depend on, and you know how to design interfaces, SLAs.

A security-minded approach to building systems: you design for safe handling of untrusted input, least-privilege access, and data protection from the start.

Operational excellence: reliability, observability, and on-call health are first-class engineering work for you.

Clear, direct communication with product, engineering, and cross-functional partners.

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