- Design, develop, and deploy enterprise-grade Generative AI solutions.
- Build end-to-end AI applications covering data ingestion, retrieval, generation, and evaluation.
- Architect and implement LLM-powered applications using modern AI frameworks and tools.
- Develop Agentic AI solutions leveraging frameworks such as CrewAI, LangChain, LangGraph, LlamaIndex, AutoGen, and Langfuse.
- Design and optimize RAG pipelines for enterprise knowledge retrieval and reasoning.
- Fine-tune foundation models using instruction tuning and supervised fine-tuning techniques.
- Evaluate model performance and implement model engineering best practices.
- Deploy and manage AI workloads in cloud environments (Azure, AWS, or GCP).
- Containerize and operationalize AI applications using Docker and Kubernetes.
- Collaborate with architects, data engineers, and product teams to deliver scalable AI solutions.
- Contribute to innovation initiatives, accelerators, and technology communities.
Technology-AI-Data science-PYTHON,Technology-AI-Generative AI-Generative AI - Basic-retrieval augmented generation (rag),Technology-OpenSystem-Python - OpenSystem-Python
