Overview:
In this role, you architect and lead scalable data architectures for cutting-edge AI and agentic systems, driving AI adoption at scale. You will mentor junior engineers, collaborate with clients and cross-functional teams, and deliver enterprise-grade ML solutions. You’ll design robust data pipelines, ensure governance and security, and push innovation across industries. This is a high-impact opportunity in a performance-driven culture that values continuous learning and mentorship. Compensation / Benefits comprehensive benefits package competitive salary world-class benefits continuous learning culture structured apprenticeship programs international collaboration across 65+ countries
Responsibilities:
Design and implement scalable data architectures for AI and agentic systems Lead development of robust data pipelines and secure data environments Mentor junior engineers and collaborate with clients and cross-functional teams Architect machine learning, agentic, and autonomous AI solutions across industries Lead MLOps/LLMOps-focused architectures for model management, observability, and automated retraining Oversee complex feature engineering and production-ready data assets Partner with QuantumBlack, AI by McKinsey, and QuantumBlack Labs to deliver enterprise-grade ML systems Drive data security, governance, and RBAC across cloud providers
Key requirements:
Degree in Computer Science/Engineering or equivalent experience 5+ years in data engineering with leadership experience Expert-level Python and SQL; ability to work with Scala/Java when needed Experience building Agentic AI, Generative AI, ML, and BI systems Knowledge of MLOps/LLMOps, CI/CD for data workflows, and IaC (Terraform) Experience with data security and governance (PII/PHI, authentication, RBAC) Strong communication skills in English Willingness to travel Strong communication and written skills Mentoring and leadership Cross-functional collaboration Python SQL Scala or Java (preferred)