Description

Detailed Roles and Responsibilities:

Role Objective (Summary)

• Act as the technology and delivery lead for all Data & AI initiatives across the organization.

• Define and implement scalable Data & AI architecture using Microsoft Azure AI and Microsoft Fabric.

• Lead the design, development, and deployment of advanced Machine Learning and AI solutions.

• Drive enterprise data engineering and ETL strategies ensuring high-quality, reliable, and scalable data pipelines.

• Collaborate with business stakeholders to identify AI use cases and translate them into impactful solutions.

• Ensure continuous optimization of models for accuracy, performance, and scalability.

• Establish best practices for AI engineering, MLOps, and AI-DevOps frameworks.

• Govern data and AI standards, ensuring compliance, security, and ethical AI practices.

• Mentor and lead cross-functional teams including data engineers, data scientists, and AI engineers

Responsibilities

Key Responsibilities
Data Engineering & ETL Management
• Design and implement robust data pipelines using Azure ecosystem and Microsoft Fabric.
• Manage ETL processes ensuring data quality, consistency, and availability.
• Optimize data workflows for performance and scalability.
Machine Learning & AI Engineering
• Develop, deploy, and maintain ML models and AI solutions.
• Implement model lifecycle management including training, validation, deployment, and monitoring.
• Drive experimentation and innovation in AI/ML techniques.
Model Optimization & Performance
• Continuously improve model accuracy, efficiency, and reliability.
• Implement performance monitoring and feedback loops.
AI DevOps (MLOps)




• Establish CI/CD pipelines for AI/ML models.
• Implement versioning, monitoring, and governance frameworks for models.
Solution Architecture
• Design end-to-end Data & AI solutions aligned with enterprise architecture.
• Ensure scalability, security, and integration with existing systems.
Stakeholder Management & Leadership
• Collaborate with business, IT, and leadership teams.
• Translate business problems into technical AI solutions.
• Lead and mentor teams, fostering a culture of innovation and excellence.

Reporting Responsibilities:
• Provide regular updates on AI initiatives, model performance, and delivery status.
• Present insights, dashboards, and AI outcomes to leadership.
• Ensure documentation of data pipelines, models, and architecture.
• Drive governance and reporting standards across Data & AI programs.

Qualifications

Key Skills & Competencies
• Solid expertise in Microsoft Azure AI and Microsoft Fabric
• Deep knowledge of Data Engineering, ETL processes, and data architecture
• Experience in Machine Learning, AI modelling, and optimization techniques
• Hands-on experience with MLOps / AI-DevOps frameworks
• Strong problem-solving and analytical skills
• Excellent stakeholder management and communication skills
• Leadership and team management capabilities
• Ability to work in a fast-paced, evolving technology landscape.

Qualifications
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field
Certifications (Preferred / Added Advantage)
• Microsoft Certified: Azure AI Engineer Associate
• Microsoft Certified: Azure Data Engineer Associate
• AI/ML certifications (preferred)
• Certifications in Data Engineering / Cloud Architecture

📌 Head - Data/ AI (India)
🏢 Nameless
📍 India