Director of Artificial Intelligence
WhiteSlips Job Management Consultants · Mumbai · onsite · Posted 27d ago
Not disclosedFresherfulltimeSourced from
About a minute. You'll make an account on the way through.
About this role
- 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 professional 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).
Sourced from foundit
Skills
data model pipelinesautomated testingObservability toolsDevSecOps practicesAI Data EngineeringDeployment Standards