- AI Data Engineering Vision
- Own the end-to-end engineering delivery of AI enabled data products in the portfolio: from user story refinement and technical design through development, testing, and production release.
- Drive data product vision alignment by partnering with Product Owners and commercial stakeholders to ensure every feature delivers measurable user value.
- Enable parametrized, automated, and reusable data/model pipelines that accelerate feature delivery and ensure interoperability across the analytics ecosystem.
- Stay current with emerging AI data engineering technologies and evaluate their applicability to International Commercial product roadmap.
- Application Development & Stakeholder Collaboration
- Partner with global commercial teams, brand leads, and regional stakeholders to deeply understand user workflows, pain points, and unmet needs.
- Translate user requirements into technical specifications, ensuring alignment between business intent and engineering execution.
- Drive iterative development cycles with rapid prototyping, user feedback loops, and continuous improvement.




- Coordinate with enterprise Data and AI Platform teams to leverage shared infrastructure while maintaining product delivery velocity.
- Engineering Excellence & Quality
- Establish and maintain CI/CD pipelines, automated testing, and deployment standards that ensure reliable, frequent releases.
- Define quality standards including test coverage targets, release readiness criteria, and production monitoring.
- Leverage observability tools to gain insights into system behavior and proactively address issues.
- Champion DevSecOps practices: embed security controls and compliance checks into development workflows
- People Leadership & Team Development
- Build and mentor a high-performing team of AI data engineers
- Set technical direction, career paths, and coaching routines; foster a culture of ownership, learning, and engineering excellence.
- Coach direct reports to adopt best practices, improve technical skills, and achieve skilled growth.
- Lead contractor and vendor support to extend capabilities and maximize delivery efficiency.
- Drive engineering maturity through design docs, architecture decision records (ADRs), code reviews, and continuous learning (labs, guilds, demos).

📌 Director of Artificial Intelligence (Mumbai)
🏢 WhiteSlips Job Management Consultants
📍 Mumbai