Director of Engineering (Data Diversity)

We are looking for an experienced Director of Engineering - Data Diversity and AI Platforms to lead the strategy, architecture, and execution of large-scale data engineering and AI platform initiatives. This role requires deep expertise in data platforms, distributed systems, AI/ML ecosystems, scalable data pipelines, GenAI infrastructure, and engineering leadership. The ideal candidate should have strong experience building enterprise-scale data and AI platforms that power intelligent, data-driven products and AI workflows. The candidate will work closely with Engineering, AI/ML, Product, Analytics, and Platform teams to enable scalable AI-ready data ecosystems and next-generation enterprise AI capabilities.
The core responsibilities for the job include the following:
Engineering Leadership:
Lead and scale engineering teams focused on data platforms, AI infrastructure, and distributed systems.
Drive engineering strategy, architecture, execution, and platform modernization initiatives.
Mentor Engineering Managers, Architects, and Senior Engineers across multiple teams.
Establish engineering best practices, delivery governance, operational excellence, and platform reliability standards.
Data and AI Platform Architecture:
Design and build scalable, reliable, and high-performance data and AI platforms.
Drive architecture for: Enterprise data lakes/lakehouse platforms, Real-time and batch data pipelines, AI/ML data ecosystems, GenAI and LLM-powered data workflows, Data observability and governance frameworks, and Intelligent automation and AI orchestration systems.
Enable scalable AI infrastructure supporting: Generative AI applications, Agentic AI workflows, RAG pipelines, AI copilots, and enterprise AI assistants.
Ensure scalability, reliability, performance, security, and governance of enterprise data and AI systems.
AI / GenAI Initiatives:
Strong understanding of: Generative AI (GenAI), Large Language Models (LLMs), RAG architectures, AI orchestration frameworks, Vector databases, AI/ML pipelines, Agentic AI systems, AI governance, and observability.
Collaborate closely with AI/ML and Data Science teams on AI platform strategy and execution.
Drive AI platform adoption, operational readiness, and enterprise-scale deployment initiatives.
Data Diversity and Governance:
Lead initiatives focused on improving data diversity, quality, accessibility, lineage, and governance across enterprise systems.
Define frameworks for metadata management, cataloging, observability, and data standardization.
Partner with AI/ML teams to ensure high-quality AI training and inference datasets.
Cross-Functional Collaboration:
Collaborate with Product, AI/ML, Analytics, Security, and Business teams to align data and AI strategies with organizational goals.
Drive executive stakeholder alignment, prioritization, and enterprise transformation initiatives.
Lead large-scale cross-functional program execution across distributed engineering teams.
Requirements:
15+ years of experience in Engineering / Data Engineering / Platform Engineering.
Strong experience building and scaling enterprise data and AI platforms.
Proven leadership experience managing large engineering organizations.
Deep understanding of: Distributed systems, Data Engineering, Cloud-native architectures, AI/ML ecosystems, Real-time streaming platforms, and Enterprise AI infrastructure.
Strong experience with enterprise-scale AI/ML or Generative AI initiatives.
Excellent stakeholder management and executive communication skills.

Experience
15-19 yrs