Aws Lambda, Machine Learning, Design Patterns, Dependency Injection, Rest Apis, Python, OOP principles, event loops, fault-tolerant cloud services, JSON serialization, modularity, Distributed System Design, asyncio, queue-based orchestration

Integration, Api Development, Python, Generative AI, LLMs, DevOps practices, Agentic frameworks

LLMs (OpenAI, Data Processing & Feature Engineering, Cloud Platforms (AWS/Azure/GCP – optional), Python, Pytorch, LangChain, NLP Concepts

Natural Language Processing, AI ML, Tensorflow, Pytorch, Python, Generative AI, Langchain, Transformers, LLMs, scikit-learn, Hugging Face, Pinecone, anomaly detection, prompt engineering, spaCy, Word2Vec, FAISS, TF-IDF, BERT, ChromaDB, Langraph

AI Integration Tools - LangChain LlamaIndex, Tensorflow, Pytorch, Machine Learning Frameworks, AI model fine-tuning techniques, Prompt engineering, AWS Bedrock, Vector Database architectures, Advanced Python programming for AI ML applications, Retrieval Augmented Generation RAG, Hugging Face, LoRA Low-Rank Adaptation techniques, Amazon SageMaker, Machine Learning architectures, Generative AI Technologies, AI system design and integration, GraphRAG methodologies, Cloud-native AI solution design, Large Language Models LLMs, AWS AI services, Agentic AI design principles

Scrum, Sql, Tensorflow, Nlp, Pandas, Pytorch, Docker, Agile, Azure, Python, AWS, embeddings, scikit-learn, vector databases, CI CD, Transformers, RAG pipelines

Distributed Computing, Hadoop, Tensorflow, Pytorch, Spark, Python, LLMs, model versioning, prompt engineering, big data tools, MLOps tools, ML frameworks

data engineering , containerization , Software Engineering, Python, agent orchestration frameworks, testing strategies, cloud platforms, LLMOps, data pipelines, machine learning engineering, observability, communication patterns, real-time context injection, control flows, cluster orchestration, AI workflows