Engineering Manager

About Peec AI

Peec AI is the analytics platform for AI search. People increasingly discover products and make buying decisions through ChatGPT, Claude, Gemini, and Google's AI Overviews instead of traditional search, and most brands have no idea where they show up in those answers. Peec gives marketing, SEO, and growth teams the data to see exactly that: how visible their brand is across AI platforms, how they compare to competitors, and where to win.

We are defining this category, and the market is moving with us. Peec is a Series A company backed by 20VC and Singular, that went from $0 to $15M ARR in 18 months, with a 100+ person team across our Berlin HQ and our New York office.

What you’ll do

• Build, mentor, and lead an elite data science team as a trusted, empathetic player-coach, while clearly communicating complex technical ideas to executives, customers, and partners

• Personally design, train, deploy, and own the models that power Peec AI’s AI Search recommendations, taking hands-on responsibility for our most business-critical ML systems

• Develop and ship novel algorithms that reverse-engineer AI search and LLM behavior, turning deep technical insight into durable, customer-facing product advantages

• Own the full ML lifecycle end-to-end — from first-principles research and rigorous experimentation to production deployment, monitoring, and continuous improvement

• Architect and evolve scalable data and ML systems, making high-leverage decisions across data pipelines, modeling approaches, evaluation frameworks, and model serving

• Write and review production-grade code at an exceptional standard, setting the technical bar for the entire organization

What we’re looking for

• 8+ years of professional data science experience, with at least 3+ years in a leadership or managerial role at a top-tier high growth startup, or FAANG level tech company (e.g., Tech Lead, EM, SDM)

• A world-class data science leader with a rare combination of deep technical mastery and proven leadership, who has built and shipped category-defining ML products in high-growth or frontier environments

• A demonstrable history of personally owning and scaling complex ML systems from raw research ideas to reliable, high-impact production deployments

• Exceptional command of Python and applied machine learning, with strong systems-level instincts spanning APIs, data pipelines, ML infrastructure, and production reliability