
Állás
· Lead
Lead C++ Engineer – Data Engine (Builder-Lead Role)
Egyéb
• Lead
• Hibrid
• Teljes munkaidő
•
Haarlem, Hollandia
Want to build the engine behind AI-powered data preparation—and stay close to the code while leading a team? Enjoy solving hard data problems and seeing your work become a product customers rely on? At AIMMS, we’re looking for a Lead C++ Engineer to build the data engine powering SENSAI Data Ready, then help grow it into a shared data layer across our optimization platform. A Role You Can Shape Good optimization starts with reliable data. With SENSAI Data Ready, supply chain analysts will work with AI agents to turn raw customer data into validated, model-ready datasets—without needing data engineering skills. Your team builds the engine that makes this possible. The core runs in modern C++; the agents and analytics tools run in Python. You’ll own how these pieces work together, making data preparation fast, reproducible and traceable. Our Lead Architect starts the C++ build; you take over technical ownership and grow the team around it. Data Ready is the starting point. As the shared data layer expands across AIMMS applications, so will your scope. What You’ll Do This is a hands-on engineering role with leadership responsibility—not a move away from coding. Build and own the engine: Write a substantial share of the C++ services, connectors, recipe execution, storage and versioning. Solve the hard data problems: Tackle SQL generation, schema drift, deterministic execution and performance on datasets of 10 million-plus rows. Connect C++ and AI: Design the interfaces between the engine and Python-based agents and analytics tools, keeping results reliable and auditable. Lead a small, growing team: Start with two engineers, set technical direction, coach through pairing and reviews, and hire as the scope grows. Shape the wider platform: Work with the Lead Architect on a persistent data layer that AIMMS applications can share. Deliver for real users: Work with Product and customers to turn messy data challenges into practical, production-ready capabilities.
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