Python, Agentic AI development, AI evaluation frameworks, Model serving and optimization, AI observability and evaluation practices, Production ML systems, Model serving infrastructure, Agentic AI systems, Agent orchestration frameworks, LLM gateways, LLM orchestration, Containerized deployments using Kubernetes, Self-hosted model deployment, Self-hosting AI models

Spring Boot, Elk Stack, Jenkins, Devops, REST, MLops, Gcp, Docker, Ansible, Elasticsearch, FastAPI, Azure, Ocr, Kubernetes, AWS, data pipelines, vector databases, Agentic AI systems

Tensorflow, Azure ML, Pytorch, Python, RAG embeddings, LLMs, scikit-learn, prompt engineering, SageMaker, vector stores, GCP Vertex AI, Cloud ML infrastructure

Sql, Nosql, Tensorflow, Rest API Development, Pytorch, Gcp, Docker, Azure, Python, Kubernetes, AWS, MLOps tools, NLP techniques, Feature stores, Data versioning

Machine Learning, Api Development, Python, AWS, LangChain, vector databases, Anthropic, NLP libraries, LangGraph, LLM orchestration frameworks, Mistral, Llama, OpenAI, LlamaIndex, RAG architectures

code optimization , Agile Software Development, Nodejs, Code Review, JIRA, Python, agent handover scenarios, multi language bot building, bot unit test cases, API integrations

Java, Github, Sql, Nosql, Nlp, Software Architecture, Hive, Python, Machine Learning Algorithms, LangChain, Generative AI, PySpark-dataframes, AI ML models, CI CD pipelines

Tensorflow, Software Development, Pytorch, Neural Networks, Pattern Recognition, Python, machine learning frameworks, Computer Science principles

Apache Spark, Kafka, Sql, MLops, Kinesis, Databricks, Python, Aws S3, AWS Bedrock, RAG frameworks, LLMs, LLMOps, Lakehouse architectures, vector databases, Pinecone, FAISS, Delta Lake