Engineering Manager, Data
Role details
Job location
Tech stack
Job description
progressive, and, importantly, a kind bunch of 850+ people from over 100 nationalities, all committed to delivering the future of business spending, together. About The Role The Data & AI Products and Data Serving teams are Pleo's two newest teams. Data & AI Products builds customer-facing features using data, AI or ML. Data Serving owns the production-grade data layer that every downstream consumer product team, AI agent, and external customer depend on for clean, reliable data. This Senior Manager role spans both teams. It is a data and engineering leadership role with a strong product backbone, designed for a builder-leader. You need to understand what good AI feature engineering looks like, what it takes to build end-to-end data products, data engineering best practice, and how to build and lead teams that do both well. You will stay close enough to the work to shape technical direction, unblock delivery, and raise the quality bar across both teams. Who You'll Be Working With And, trust standards across AI feature development by implementing evaluation methodologies, production monitoring processes, responsible AI practices and more. - Ensure the serving layer meets the reliability and latency requirements of production AI features, product teams, and external customers directly accessing their data. - Manage resourcing and hiring across both teams through a period of growth. - Represent both teams in leadership and cross-functional discussions, translating technical progress and blockers into clear decisions needed. - Partner with the Manager of GenAI Platform to ensure product demand shapes the platform roadmap. Our tech stack currently includes AWS, Kotlin, Python, Kubernetes, LiteLLM, BrainTrust, Temporal, LLM APIs and more. You do not need to be an expert across all of these, but need enough familiarity to follow technical discussions and make good trade-off decisions. What You Bring - Proven experience leading cross-functional teams
Requirements
building AI-powered or data-intensive customer-facing products. - Technical depth in at least one of: AI product engineering, real-time reporting/analytics data APIs, or ML systems - enough to hold credible technical conversations and make good hiring and architecture decisions. - Experience building or substantially growing teams enabling you to hire, develop, and retain senior technical talent in a competitive market. - Strong product and business acumen. You can work with PMs and designers to shape a roadmap, not just execute one handed to you. - Track record shipping with quality under velocity pressure (AI features and production APIs both carry high trust requirements from customers). - Comfortable managing across distinct te