DigitalOcean is a cutting-edge technology company focused on simplifying cloud and AI for developers. They are seeking a VP of Engineering to lead the architecture and execution of their AI-native Data Cloud platform, ensuring platform reliability and developer adoption while driving business outcomes.
Responsibilities:
- Architecture And Delivery Of a Unified Platform Spanning
- Ingestion (connectors, CDC, streaming)
- Storage (object, OLAP, vector, graph)
- Processing (ELT pipelines, real-time and batch)
- Query & analytics (SQL, hybrid search, RAG)
- Governance (catalog, lineage, versioning, access control)
- Deliver GA-grade services with strong SLAs, cost efficiency, and simplicity
- Drive roadmap aligned to Digital Native Enterprise (DNE) customers
- Establish and manage clear metrics: adoption, retention, ARPU, performance, reliability
- Build and scale a high-performing global organization (US and India)
- Implement single-threaded ownership (STO) across services
- Partner deeply with Product, GTM, and Platform Engineering
- Launch a cohesive Data Cloud platform—not a collection of fragmented services
- Achieve meaningful adoption across AI-native workloads (RAG, inference, analytics)
- Reduce developer time-to-value from weeks to hours
- Establish clear differentiation versus hyperscalers on simplicity and cost
Requirements:
- Proven track record of building and operating cloud-scale data platforms (OLAP, lakehouse, streaming, or ML systems), with strong architectural judgment across storage, processing, and query layers
- Experience integrating open-source ecosystems (e.g., Spark, Airflow, dbt) into managed cloud services at scale
- Experience with AI/ML data pipelines (feature stores, embeddings, RAG)
- Demonstrated ability to operate in ambiguity, make high-quality decisions with incomplete data, and drive multi-quarter execution with measurable outcomes
- Proven experience scaling engineering organizations and delivering under real-world constraints
- You have personally driven complex distributed systems from concept to production—not just managed teams that did