Data Engineer for AI Applications

About the role

QuantumBlack, AI by McKinsey is looking for a Data Engineer to build the data foundation for cutting‑edge AI applications that leverage large language models, retrieval systems and emerging agentic architectures. You will join a high‑performance team that collaborates closely with clients and cross‑functional experts to turn raw data into reliable inputs for AI‑driven solutions.

Key responsibilities

• Design, develop and maintain scalable data pipelines that feed machine‑learning, agentic and autonomous AI systems.
• Assess data landscapes, apply data‑quality best practices and prepare datasets for LLM‑based and retrieval‑augmented models.
• Manage secure data environments, ensuring compliance with privacy and security standards.
• Collaborate with engineers, data scientists and client stakeholders to translate hypotheses into engineered features.
• Contribute to research and development initiatives focused on next‑generation AI infrastructure.

Required profile

• Strong analytical mindset with a passion for building robust data solutions.
• Ability to work in a fast‑paced, collaborative environment and adapt to evolving technical challenges.
• Commitment to ethical AI practices and continuous learning.

Required skills

• Experience with large language models (LLMs) and retrieval‑augmented systems.
• Knowledge of building secure, scalable data pipelines.
• Understanding of data quality fundamentals and feature engineering for AI.

What we offer

• Continuous learning through structured apprenticeship and mentorship programs.
• Opportunities to influence AI product development from day one.
• Competitive salary and a comprehensive benefits package supporting holistic well‑being.