AI TIC Head - Director AI Research

We are creating a world-class AI Centre of Excellence to drive breakthrough

innovation and commercialize next-generation AI solutions. As the Head of AI TIC,

you will define the AI vision, lead state-of-the-art research, and scale enterprise-

grade AI products from concept to global deployment.

This is a high-impact leadership mandate for a visionary who thrives on building

from scratch, scaling teams, and delivering AI solutions that transform

industries. You will have full autonomy to shape the roadmap, architect the

ecosystem, and position the organization as a global leader in AI innovation.

Impact & Opportunities

• Global Influence: Drive AI strategy that sets industry benchmarks.

• Commercialization: Take AI products from research prototypes to market-

ready solutions at scale.

• Elite Team Building: Recruit and mentor top-tier talent from leading AI labs

and research institutions.

• Thought Leadership: Represent the organization at global AI conferences,

research forums, and strategic partnerships.

Key Responsibilities

1. AI Strategy & Vision

• Define and execute a long-term AI roadmap aligned with business

transformation and global expansion.

• Champion Generative AI, LLMs, and advanced ML for high-value enterprise

applications.

• Establish frameworks for ethical AI, bias mitigation, and compliance.

2. Architecture & Innovation

• Architect a scalable AI ecosystem, including LLMOps/MLOps pipelines

and secure enterprise integration.

• Lead development and fine-tuning of proprietary LLMs, multimodal models,

and retrieval-augmented systems.

• Ensure robust data governance and architecture for AI-driven insights.

3. Delivery & Scaling

• Proven track record of delivery: Drive rapid prototyping and transition to

production-grade deployments with measurable business impact.

• Scale AI COE: Build and expand the AI TIC to support multiple enterprise

initiatives simultaneously.

• Implement CI/CD for ML, automated monitoring, and performance

optimization using ONNX, DeepSpeed, and similar frameworks.

Public

• Proven technology transfer from research to products

4. Leadership & Cross-Functional Collaboration

• Build and scale high-performing teams of AI researchers, engineers, and

ML Ops professionals.

• Foster a culture of innovation, velocity, and technical excellence.

• Collaborate with product, engineering, and business leaders to embed AI into

core workflows.

• Research team leadership experience (15-30 people)

Qualifications & Experience

• Education: Masters/Ph.D. from a top-tier institute (IIT, IISc, MIT, Stanford,

etc.) in Computer Science, AI, or related field.

• Research publications in top-tier AI conferences/journals such as NeruralIPS,

ICLR, ICML, AAAI, and CVPR with demonstrated leadership in publishing top-tier

research in LLMs, multimodal models or related areas.

• Patents filed / granted with commercial impact is desired.

• Experience: 15–21 years in technology leadership, with 5+ years in AI/ML

and Generative AI.

• Proven success in:

• Building and scaling AI teams and COEs
• Commercializing AI products from research to market
• Delivering enterprise-grade AI solutions with measurable impact

• Deep expertise in LLMs, Generative AI, NLP, Computer Vision, and modern

AI frameworks (PyTorch, TensorFlow, Hugging Face).

• Hands-on experience with cloud AI platforms (AWS SageMaker, Azure ML,

GCP AI).

• Strong understanding of MLOps/LLMOps, CI/CD for ML, and security in AI

systems.

• Exceptional communication and executive presence.