As the Head of AI, 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.
Qualifications & Experience
Education: Master’s/Ph.D. from a top-tier institute (IIT, IISc, MIT, Stanford, etc.) in Computer Science, AI, or related field.
8-12 patents filed, 5+ granted with commercial impact
10+ publications in top-tier AI conferences/journals
Experience: 12–15+ 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.
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)
Immediate to 15 Days
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