Required Qualifications : -
- Bachelor’s or Master’s degree in Computer Science, AI / ML, or related fields; PhD preferred.
- 15 to 18 years of experience in technology consulting or product engineering, with at least 5 years in AI / ML practice leadership.
- Proven success in modernizing enterprise applications using AI / ML, cloud-native architectures, and microservices .
- Deep expertise in Generative AI (LLMs, Transformers, RAG, Multi-Agent Systems) and emerging Agentic AI frameworks .
- Proven expertise in :
- AI / ML architecture, LLMs, RAG / GraphRAG pipelines, and agentic workflows.
- Cloud ecosystems (AWS, Azure, GCP) and modernization tools (Azure Migrate, AWS Refactor Spaces, etc.).
- Python, Node.js, or Java with hands-on experience in AI libraries (LangChain, HuggingFace, PyTorch, TensorFlow).
- Knowledge graphs, vector search, and orchestration frameworks.
- Hands-on understanding of cloud AI ecosystems (AWS Sagemaker, Azure AI, GCP Vertex AI) .
- Strong experience with MLOps, LLMOps, and AI governance .
- Excellent stakeholder management, business acumen, and communication skills.