Title : Sr. 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.

- 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).